Jobs at Djinni

Overview

Imagine this: you build projects from scratch, from IoT devices to smart solutions for energy and security. We’re looking for an Embedded Engineer. Lviv, relocation support provided! No legacy, with a team that truly helps you level up. If you’re interested in growing in low-level Embedded development.

Main Responsibilities

— Participate in the full embedded software life cycle: design, implementation, code reviews, documentation, testing, and validation

— Analysis and systematic problem-solving for SW-reported issues

— Cooperate with electrical engineers

Mandatory Requirements

— 1-3 years of professional experience

—C/С++ Programming Language on embedded systems

— Experience with STM32/SiLabs/Rigado/Microchip microcontrollers

Interfaces and protocols (UART, I2C, SPI, ModBus, CAN, USB, Ethernet,

etc.)

— Embedded Real-time operating systems

— Experience with Linux

— Experience in image, video, and signal processing

— Version control systems, task tracking systems

— Understanding of electrical schematics

Would be a plus

— Experience in networking: TCP, UDP, MQTT, TLS

— Understanding of cloud connectivity/IoT concepts and applications

— Automated and regression testing

We offer

— Competitive salary with regular reviews

— Modern projects with cutting-edge technologies

— Excellent space for your personal and professional development

— Low level of bureaucracy with a lack of multi-level management

— Attractive work environment: The modern and stylish office with ergonomic workstations, creative zones, and innovative spaces

— Paid vacations and sick leaves

— Accountant support

— Educational Events

— Free English classes

— Amazing team buildings

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the client

Our client is developing technology to make industrial environments safer and reduce the risk of accidents through proactive monitoring.

The Ukrainian engineering team is building a next-generation industrial safety platform combining Computer Vision, Machine Learning and IoT.

About the role

We are looking for a Middle Systems / Software Engineer to work on the performance-critical core of a real-time Computer Vision platform.

This is not a typical Python Backend role. The main challenge is building and optimising the systems underneath the CV/ML engines — where performance depends on memory, processes, concurrency, data movement, CPU/GPU utilisation and low latency.

You will work on the runtime that executes CV pipelines as a graph of processing stages, with latency measured in milliseconds. You will deal with shared memory, zero-copy data transfer, inter-process communication and process orchestration.

What matters most to us

We are open to engineers coming from C++, Python, Go or similar backgrounds.

The programming language itself is not the main selection criterion. What matters much more is a strong systems engineering mindset and experience understanding what is happening inside a system.

For example, we are particularly interested in engineers who have worked with problems such as:

• reducing unnecessary memory copies;
• optimising CPU/GPU utilisation;
• investigating latency spikes and performance bottlenecks;
• working with processes, threads and concurrency;
• debugging race conditions and difficult low-level issues;
• profiling applications and identifying bottlenecks;
• designing efficient data-processing pipelines;
• working with large amounts of data moving through several processing stages;

• optimising algorithms or runtimes for performance.

   

A candidate does not necessarily need to have worked with exactly the same technologies before.

For example, experience with CUDA, C++, GPU optimisation, real-time processing, robotics, computer vision, video pipelines, scientific computing or other performance-sensitive systems can be highly relevant.

What you’ll work on

• Collaborate with CV/ML engineers to turn model inference code into reliable production pipeline stages.
• Develop and optimise the core Pipeline Engine — an in-process, real-time runtime executing the CV pipeline as a graph of stages.
• Work with zero-copy shared-memory pools for passing frames between processes.
• Develop and optimise low-latency ZeroMQ communication for control messages, metadata and synchronisation.
• Work with pipeline metadata and serialisation boundaries.
• Analyse and improve CPU, memory and latency performance.
• Profile, debug and troubleshoot complex runtime issues.

• Contribute to the architecture and evolution of the real-time processing infrastructure.

   

Requirements

Must-have

• Commercial experience as a Software Engineer / Systems Engineer / C++ Engineer / Python Engineer or similar.
• Strong systems engineering mindset and understanding of:
  • processes and concurrency;
  • memory ownership and data movement;
  • latency vs throughput trade-offs;
  • performance bottlenecks;
  • profiling and debugging;
  • failure modes of complex systems.
• Experience working with performance-sensitive or latency-sensitive systems.
• Experience with at least one of C++, Python, Go or a similar programming language.
• Python is used in the platform, but it does not need to be your primary language. Strong C++ / systems experience is equally relevant.
• Solid Linux fundamentals.

• Solid experience with Docker and containerised environments.

   

Nice-to-have

• CUDA, including IPC handles and stream synchronisation.
• C/C++ or Go.
• OpenCV.
• GStreamer, FFmpeg or RTSP.
• ZeroMQ.
• Shared memory / zero-copy architectures.
• FlatBuffers or other binary serialisation formats.
• Experience building or operating camera/video pipelines.

What we offer

• Competitive compensation.
• Benefits package.
• Strong engineering team.
• Opportunity to work on challenging real-time Computer Vision infrastructure.
• Meaningful industrial safety use case.
• Technical challenges and opportunities for professional growth.

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the client

Our client is developing technology to make industrial environments safer and reduce the risk of accidents through proactive monitoring.

The Ukrainian engineering team is building a next-generation industrial safety platform combining Computer Vision, Machine Learning and IoT.

About the role

We are looking for a Middle Systems / Software Engineer to work on the performance-critical core of a real-time Computer Vision platform.

This is not a typical Python Backend role. The main challenge is building and optimising the systems underneath the CV/ML engines — where performance depends on memory, processes, concurrency, data movement, CPU/GPU utilisation and low latency.

You will work on the runtime that executes CV pipelines as a graph of processing stages, with latency measured in milliseconds. You will deal with shared memory, zero-copy data transfer, inter-process communication and process orchestration.

What matters most to us

We are open to engineers coming from C++, Python, Go or similar backgrounds.

The programming language itself is not the main selection criterion. What matters much more is a strong systems engineering mindset and experience understanding what is happening inside a system.

For example, we are particularly interested in engineers who have worked with problems such as:

• reducing unnecessary memory copies;
• optimising CPU/GPU utilisation;
• investigating latency spikes and performance bottlenecks;
• working with processes, threads and concurrency;
• debugging race conditions and difficult low-level issues;
• profiling applications and identifying bottlenecks;
• designing efficient data-processing pipelines;
• working with large amounts of data moving through several processing stages;

• optimising algorithms or runtimes for performance.

   

A candidate does not necessarily need to have worked with exactly the same technologies before.

For example, experience with CUDA, C++, GPU optimisation, real-time processing, robotics, computer vision, video pipelines, scientific computing or other performance-sensitive systems can be highly relevant.

What you’ll work on

• Collaborate with CV/ML engineers to turn model inference code into reliable production pipeline stages.
• Develop and optimise the core Pipeline Engine — an in-process, real-time runtime executing the CV pipeline as a graph of stages.
• Work with zero-copy shared-memory pools for passing frames between processes.
• Develop and optimise low-latency ZeroMQ communication for control messages, metadata and synchronisation.
• Work with pipeline metadata and serialisation boundaries.
• Analyse and improve CPU, memory and latency performance.
• Profile, debug and troubleshoot complex runtime issues.

• Contribute to the architecture and evolution of the real-time processing infrastructure.

   

Requirements

Must-have

• Commercial experience as a Software Engineer / Systems Engineer / C++ Engineer / Python Engineer or similar.
• Strong systems engineering mindset and understanding of:
  • processes and concurrency;
  • memory ownership and data movement;
  • latency vs throughput trade-offs;
  • performance bottlenecks;
  • profiling and debugging;
  • failure modes of complex systems.
• Experience working with performance-sensitive or latency-sensitive systems.
• Experience with at least one of C++, Python, Go or a similar programming language.
• Python is used in the platform, but it does not need to be your primary language. Strong C++ / systems experience is equally relevant.
• Solid Linux fundamentals.

• Solid experience with Docker and containerised environments.

   

Nice-to-have

• CUDA, including IPC handles and stream synchronisation.
• C/C++ or Go.
• OpenCV.
• GStreamer, FFmpeg or RTSP.
• ZeroMQ.
• Shared memory / zero-copy architectures.
• FlatBuffers or other binary serialisation formats.
• Experience building or operating camera/video pipelines.

What we offer

• Competitive compensation.
• Benefits package.
• Strong engineering team.
• Opportunity to work on challenging real-time Computer Vision infrastructure.
• Meaningful industrial safety use case.
• Technical challenges and opportunities for professional growth.

We are looking for a Prompt Spec Engineer who will define how our AI systems communicate, reason, and deliver high-quality outputs across products powered by LLMs.
 

You will be responsible for designing prompt/spec architectures, building evaluation systems, and ensuring that AI responses are consistent, reliable, and production-ready across RAG systems, AI agents, and automation workflows.

What you will do:
 

• Design and evolve prompt/spec architecture for AI products, LLM services, RAG systems, and AI agents, defining prompt structures, model behavior rules, response formats, and quality criteria.
• Develop, optimize, and adapt prompts for different LLMs and use cases, considering output quality, context limitations, cost, and system stability.
• Build and maintain AI evaluation processes including test scenarios, golden datasets, regression testing, and A/B experiments for LLM performance measurement.
• Analyze AI outputs, identify root causes of issues (hallucinations, missing context, retrieval problems, incorrect or unsafe responses), and define improvements.
• Collaborate with AI Engineers and Product Managers to implement prompt solutions into production systems, RAG pipelines, AI agents, and automation workflows, translating business needs into technical specifications.
• Work with LLM evaluation and monitoring tools (such as PromptFoo, Langfuse, and similar solutions) to track metrics, prompt versions, response quality, and system performance.
• Create and maintain structured documentation: prompt specs, evaluation frameworks, usage guidelines, limitations, and best practices for safe and reliable AI behavior.

What we expect from you:
 

• 2+ years of experience in LLM-related roles such as Prompt Engineering, AI Product Operations, AI Evaluation, or similar.
• Hands-on experience designing and optimizing prompts for different LLMs with a strong understanding of model behavior, strengths, and limitations.
• Experience building prompt/spec systems including prompt structure design, behavior rules, response formatting, testing, and versioning.
• Strong experience in AI evaluation: test case design, output analysis, issue detection, and iterative improvement of model performance.
• Understanding of RAG systems, AI agents, structured outputs, tool calling, and principles of reliable LLM system design.
• Ability to collaborate with engineering and product teams, translate business requirements into AI specifications, and document solutions clearly and consistently.
• Upper-Intermediate (B2+) English 
   

What we offer

• Competitive compensation depending on experience
• Work on production-level AI systems (LLMs, RAG, AI agents, automation workflows)
• Office-based work in Lviv with the possibility of a hybrid schedule.
• Direct impact on AI product quality and system behavior
• Access to modern LLM tools and evaluation frameworks
• Professional growth in a fast-moving AI-focused environment
• Opportunity to shape prompt engineering standards inside the company
• Relocation support for candidates from other cities, including assistance with moving and adaptation in Lviv.

Job Description
Front-End Development

Strong commercial experience with React
Proficiency in TypeScript
Experience building applications using Next.js
Experience developing and documenting reusable UI components with Storybook
Ability to interpret and implement designs from Figma
Experience writing unit and component tests using Jest
Strong knowledge of modern HTML and CSS, including CSS custom properties, responsive design, Flexbox and CSS Grid
Understanding of accessibility, browser compatibility and front-end performance best practices
Back-End Development

Strong commercial experience with ASP.NET Core and C#
Experience designing and developing secure, maintainable REST APIs
Experience with Azure Functions and serverless application development
Knowledge of Azure API Management
Experience working with Microsoft SQL Server, including database design and query optimisation
Experience working with Azure Cosmos DB
Understanding of authentication, authorisation and API security, ideally Duende Identity Server
Job Responsibilities
Design, implement and unit test core application components running on Azure
Drive and participate in the functional design
Contribute to the review and analysis of business requirements and development of code reviews and technical designs/specifications
Participate in SCRUM

Department/Project Description
The client is a holding company that administers association football clubs including Manchester City F.C. As for the product, it is mancity.com website and all innfrastructure around. We are using Scrum. Technologies/Tools: - Back-end: C#, .Net; ASP.NET; ASP.NET Web API; Umbraco; MS SQL. - Front-end: HTML/CSS, Angular, WebPack. - Other: Jira, Git, Docker, MS Azure.

Requirements

• 2+ years of commercial experience with Python (Django, DRF, FastAPI)
• Strong knowledge of Python 3.8+
• Solid understanding of web technologies, REST APIs, and client-server communication
• Basic knowledge of React and understanding of frontend development principles
• Good knowledge of Docker and Docker Compose
• Basic understanding of deployment and CI/CD processes; experience with GitHub Actions or similar tools
• Confident Git skills, including reading and reviewing teammates code
• English – Intermediate level or higher (able to participate in technical discussions)

Responsibilities

• Develop and maintain backend applications using Python (FastAPI, Django, DRF)
• Design and implement new features and REST APIs based on business requirements
• Maintain, optimize, and improve the existing codebase for stability and performance
• Develop and maintain frontend features using React
• Participate in code reviews and contribute to improving code quality and development processes
• Assist with deployments, CI/CD pipelines, and basic DevOps tasks

Nice to Have

• Ability to work independently while actively participating in team discussions and brainstorming sessions
• Experience with AWS infrastructure and cloud services

Profisea is a boutique DevOps and Cloud company — AWS Premier Partner specializing in Cloud Architecture, DevOps, DevSecOps and FinOps.

We are looking for a Customer Success Specialist who will work closely with clients using the Uniskai platform, helping them get the most value from the product and ensuring a great customer experience.

This role is perfect for someone who enjoys communicating with people, solving problems, and learning about cloud technologies.

We are open to junior candidates and applicants without prior experience who are motivated to learn and grow in the cloud and DevOps environment.
 

What you will do:

Communicate regularly with clients using the Uniskai platform.

Check if clients are satisfied with the platform and help them use its features effectively.

Collect customer feedback about the product and user experience.

Help clients discover and use platform features and services.

Identify issues or improvement opportunities and share them with internal teams.

Coordinate technical support when needed.

Organize calls or meetings with DevOps or development teams if technical assistance is required.

Track client requests and ensure follow-up.

What we expect:

English — Fluent.

Strong communication skills and client-oriented mindset.

Good organizational skills and attention to detail.

Ability to work with multiple tasks.

Interest in technology, cloud or DevOps will be a plus.

Experience with SaaS platforms, customer support or project coordination will be a plus but not required.
 

What we offer:

Opportunity to be part of a growing company and to grow with us

Being at the forefront of the DevOps and Cloud services industry

Great compensation 

Professional working environment where you will be an essential member of our team

About Project

It is a mobile accounting app for sole traders, freelancers and self-employed workers — income, expenses and tax handled from a phone in minutes rather than evenings.

Every year, hundreds of thousands of self-employed people type "can I claim my phone bill" into Google and land on something written by a content farm, out of date, or aimed at accountants rather than at them. Being the clearest, most accurate answer to those questions is one of the most durable growth assets this business can build — and it compounds while paid channels don't.

The job in one line

You own our written content: what we publish, why, whether it's accurate, and whether it brings us users.

What you'll do

- Own the content strategy and calendar. Build it around real search demand and real user questions, not topics that sound good. Publish to an agreed cadence (4–8 substantial pieces a month) across blog, guides, landing pages, email.
- Win high-intent search. Research and prioritise keywords around allowable expenses, Self Assessment, VAT, deadlines, sole trader vs limited company, and the specific trades and professions we serve. Own on-page SEO, internal linking, content refreshes and technical basics in partnership with Engineering / an SEO consultant. 
- Meet the accuracy bar this subject demands. Tax content is exactly what Google treats as "your money or your life" — it needs demonstrable expertise, named authors, review credits and current dates to rank at all, and it needs to be right regardless of ranking. Every piece touching tax rules, thresholds or figures goes through [our accountant / compliance sign-off] before publishing, and gets re-checked each [April] when rates change.
- Build the deadline content machine. 31 January Self Assessment, the 5 April year end, quarterly VAT/MTD deadlines and the April Budget changes are our peaks. The January content set is written, reviewed and live by November, not drafted in January.
- Own lifecycle and in-product copy. Onboarding emails, activation and re-engagement sequences, deadline reminders, release notes, app store listing copy, plus in-app microcopy in partnership with Product. Measured on activation and retention, not on open rates alone.
- Run the writers. Brief, commission and edit freelance writers and subject-matter contributors [budget: specify], and hold a consistent editorial standard and tone of voice across everything we publish.
- Set the tone of voice. Write and maintain the style guide — plain English, no jargon, no scaring people about HMRC, no condescension about money. Everyone else in the company writes to it.
- Supply the other channels. Turn each substantial piece into raw material for social and creator briefs, and maintain the guides, checklists and templates that Support and Sales send to users.
- Report honestly. Organic sessions and rankings, content-attributed sign-ups and paid conversions, email-to-activation rates, and which pieces earn their keep. Retire or rewrite what doesn't.

 What we're looking for

- 3+ years in content marketing or editorial for a B2C or SaaS product, with responsibility for results rather than output volume.
- Excellent native-standard written English, and the ability to make a dull technical subject genuinely clear. Portfolio of published work required.
- Practical SEO competence: keyword research, search intent, on-page optimisation, content refresh strategy, and comfort in GA4 / Search Console / Ahrefs / Semrush.
- Editing experience — you can improve someone else's draft and give feedback a freelancer will accept.
- Numerate, precise, and willing to check a figure rather than assume it. You'll be corrected by an accountant regularly and won't take it personally.
 

Nice to have

- Experience writing about UK tax, accounting, payroll or personal finance — or an AAT / bookkeeping background.
- You are or have been self-employed, freelance or a sole trader.
- Lifecycle email experience in a real tool (Braze / Customer.io / Klaviyo / Intercom).
- ASO / app store listing optimisation.
- Comfortable in a CMS and with light HTML; experience with a headless setup.
- Experience building a content operation from a standing start.

*Rapidum is an equal opportunities employer. We assess every application against the requirements above and nothing else.*
 

Location: Remote (UK-based) 
 

About Project

It is a mobile accounting app built for people who never wanted to do accounting: sole traders, freelancers and self-employed workers who need their income, expenses and tax handled from their phone in minutes, not evenings.

Our users aren't finance professionals. When something doesn't add up, it's their own money and their own tax return on the line — so support isn't a cost centre here, it's the product. A calm, accurate answer within minutes is the difference between a user who renews and a one-star review.

The job in one line

You own the support function: every conversation a user has with us, the systems behind those conversations, and the numbers that prove it's working.

What you'll do

- Run the front line. Own in-app chat, email, app store reviews and social DMs. Target: first response under [1 working hour] in business hours, 90% of conversations resolved without escalation.
- Hit and defend the numbers. CSAT ≥ [4.5/5], contact rate per 100 active users trending down quarter on quarter, app store rating ≥ [4.5], median resolution time inside [4 hours]. Weekly reporting, no vanity metrics.
- Build the self-serve layer. Write and maintain the help centre, in-app guides and macros so that the [top 20] recurring questions stop becoming tickets at all. Deflection is the main lever once user numbers grow.
- Hold the advice boundary. You explain how the app works, what a figure means and where it came from — you do not give tax advice. You'll own the escalation path to our qualified accountant [/ partner practice] and the standard wording that keeps us on the right side of that line.
- Bridge to Engineering and Product. Reproduce and triage bugs properly (steps, device, app version, screenshots), escalate with severity that means something, chase to resolution and close the loop with the user. Bring Product a monthly digest of the top pain points with volumes attached — not anecdotes.
- Handle peak season. Late January Self Assessment, the 5 April year end and quarterly VAT/MTD deadlines produce spikes several times normal volume. You plan cover, prepare canned responses and staffing before they hit, not during.
- Protect user data. Verify identity before discussing an account, handle personal and financial data under UK GDPR, and escalate suspected data or security incidents immediately per our process.
- Rescue accounts. Spot users about to churn or asking for refunds, and turn what you can around. Report honestly on what you couldn't.
- Write the playbook. Document the process as you build it — SOPs, escalation matrix, tone-of-voice guide — so the next two support hires can be onboarded in days, not months. You'll hire and lead them within 12 months.

What we're looking for

- 3+ years in customer support for a consumer app or SaaS product, including at least 1 year owning metrics rather than just handling tickets.
- Hands-on with a support platform (Intercom, Zendesk, Crisp, Freshdesk or similar): macros, help centre, automations, reporting — you've configured it, not just typed into it.
- Numerate and comfortable around money: invoices, expenses, VAT, tax deadlines. You don't need to be an accountant, but you must not be nervous about numbers.
- Written English that is clear, warm and plain — you can explain a tax figure to someone in a van at 7am without jargon or condescension.
- Calm under pressure with upset users, and honest when we've got something wrong.
 

Nice to have

- Experience supporting a fintech, accounting, payroll or tax product.
- AAT / bookkeeping study, or practical experience with HMRC Self Assessment, MTD, VAT.
- Built a help centre or support function from scratch.
- Mobile-specific support experience: app store review management, release cycles, device-level debugging.
 

*Rapidum is an equal opportunities employer. We assess every application against the requirements above and nothing else.*
 

Location - Remote (UK-based) 
Reports to[CTO / Head of Engineering
 

About the Project:

It is a mobile accounting app for sole traders, freelancers and self-employed workers — income, expenses and tax handled from a phone in minutes rather than evenings.

Behind a simple app sits the complicated part: bank feeds that stop syncing, receipts that scan wrong, subscriptions that don't renew, a figure that's off by £40 and nobody can say why. That's your side of the house. When a user's tax number looks wrong, someone has to prove what actually happened — in the data, not in the conversation.

The job in one line

You are tier 2: everything customer support can't resolve stops with you, and everything Engineering shouldn't be interrupted by stops with you too.

What you'll do

- Own tier-2 escalations end to end. Take what front-line support can't close, investigate it properly and either fix it, work around it, or hand Engineering a ticket they can act on immediately. Target: [90%] of escalations resolved or reproduced within 1 working day.
- nvestigate in the data, not by guesswork. Read logs, trace requests, query the database (read-only SQL), check API responses and reconcile what the app displayed against what was actually recorded. Every escalation you pass on carries a clear reproduction path and evidence.
- Run bank feed and integration failures. Open Banking connections drop, banks change formats, tokens expire, third-party providers have outages. You own diagnosis, the vendor conversation, and the honest message to affected users.
- Triage mobile crashes and releases. Monitor crash and error reporting, spot regressions after a release before the reviews do, and verify fixes on real devices across iOS and Android versions.
- Own billing and store issues. Failed payments, App Store / Google Play subscription problems, duplicate charges, refunds, entitlement mismatches — resolve them and reconcile with Finance.
- Manage incidents. Be the person who declares one: assess impact, notify users and the team, keep the status page current, coordinate to resolution, then write the post-incident review with a root cause and actions that actually get done.
- Cut the ticket volume at source. Turn recurring escalations into permanent fixes: bug reports Engineering prioritises, product changes, internal diagnostic tooling, and written playbooks that let tier 1 handle the case themselves next time. Success looks like fewer escalations reaching you each quarter, not more.
- Handle deadline peaks. Late January Self Assessment, the 5 April year end and quarterly VAT/MTD deadlines turn every technical fault into an urgent one. Cover, monitoring and rollback plans get agreed before those windows, not during.
- Guard data and access. Verify identity before touching an account, work under UK GDPR with financial and personal data, keep production access to what your role requires, and escalate suspected security or data incidents immediately.

 What we're looking for

- 3+ years in technical support, application support or a tier-2/escalations role for a live software product — ideally consumer-facing.
- You can read a log, write a SQL SELECT, call an API endpoint with Postman / curl and inspect a JSON response without help.
- Practical experience with bug triage alongside an engineering team: severity, reproduction, prioritisation, verification.
- Experience with third-party integrations or API failures, and dealing directly with vendor support.
- Written English clear enough to explain a technical cause to a user in plain terms and to a developer in precise ones.
- Calm and methodical during outages — no panic, no guessing, no silence.
 

Nice to have

- Fintech, accounting, payroll or payments background — bank feeds, Open Banking, reconciliation, double entry.
- Mobile support experience: crash reporting, device fragmentation, store release cycles, RevenueCat or similar subscription tooling.
- Scripting for diagnostics or reporting (Python / SQL / Bash).
- Experience setting up monitoring, alerting or an internal admin/diagnostic tool.
- Any incident-management framework in practice, on-call rotations, blameless post-mortems).

What we offer

- £20 000 plus a bonus.
- A function you own and build, with the tooling budget and production access to do it properly.
- Remote  working with core hours 09:00–18:00 UK. On-call is limited to release windows and tax-deadline peaks, compensated at rate.
- Annual leave plus UK bank holidays, with peak-season cover agreed in advance.
- Direct line to Engineering — your bug reports go into the sprint, not into a backlog nobody reads.
- Tools and training funded, including certifications relevant to the role.

*Rapidum is an equal opportunities employer. We assess every application against the requirements above and nothing else.*
 

The Mission
Are you a cloud architect who finds beauty in a perfectly orchestrated pipeline? Do you believe that “manual” is a four-letter word? We are looking for a Senior SRE specialized in BI Ecosystems to join our mission-critical Infrastructure team.
In this role, you won’t just “maintain” systems; you will be the master weaver connecting our advanced Data Analytics tools with a rock-solid, automated GCP/AWS backbone. You will bridge the gap between traditional Business Intelligence and modern Cloud Engineering, ensuring our data flows are fast, our visualizations are seamless, and our infrastructure is invisible.

What You Will Do
1. Master the Orchestration (GCP & GKE)
You will take full ownership of our Google Kubernetes Engine (GKE) clusters. This isn’t just
about pods and services; you’ll manage advanced networking (VPC Service Controls, Shared VPC) and high-availability node configurations to ensure our data platforms never skip a beat.
2. Advance Data Architectures (Lakehouse)
You will design and support a unified Data Lakehouse architecture by integrating BigQuery and Cloud Storage. Your mission is to break down silos, ensuring that our raw data and analytical models coexist in a single, high-performance ecosystem. You will implement robust governance and security policies that ensure data quality and accessibility, providing a “single source of truth” that is both scalable and cost-effective
3. Evangelize Infrastructure as Code (IaC)
Our goal is 100% immutability. You will use Terraform to automate the entire lifecycle of our
GCP resources—from Compute Engine and Cloud Run to Cloud SQL—ensuring consistency
across Dev, Staging, and Production.
4. Empower DataViz Excellence
You will be the enabler for our Data Analysts. You’ll deploy, optimize, and scale Qlik Sense,
Tableau, or Similars environments on GCP, handling everything from SSO/IAM authentication to high-performance connectivity with our backend data sources.
5. Hybrid Cloud & Legacy Modernization
Complexity is our playground. You will manage critical AWS resources (EC2, S3) and ensure
seamless interoperability with GCP. Simultaneously, you will lead the charge in migrating legacy monolithic systems into modern, microservices-based architectures.
6. Data Engineering Collaboration
Working side-by-side with Data Engineers, you’ll help build and maintain robust pipelines using Cloud Dataflow, Cloud Composer (Airflow), and BigQuery. You ensure that the “plumbing” of our data world is leak-proof and high-performing.
7. Reliability, Security & FinOps
● CI/CD: Design sophisticated pipelines (GitLab CI/GitHub Actions) integrating DevSecOps best practices.
● Observability: Implement deep monitoring using Google Cloud Operations Suite and Grafana.
● FinOps: Be the guardian of our budget, identifying and eliminating cloud waste through
smart optimization.

Who You Are (Requirements)
● Cloud Expert: Proven experience managing complex environments in Google Cloud Platform (GCP) and AWS.
● Data Architect: Deep understanding of Data Lakehouse models and governance.
● Kubernetes Pro: Deep knowledge of GKE, including advanced networking and security policies.
● Terraform Ninja: Ability to write modular, scalable, and secure IaC.
● BI Infrastructure Savvy: Experience deploying and tuning enterprise visualization tools (Tableau, Qlik, or Power BI).
● Automation Mindset: Strong scripting skills (Python, Bash, or Go) and mastery of CI/CD engines.
● Data-Driven: Familiarity with Big Data tools like Airflow, BigQuery, and Dataflow.
● Security-First: Solid understanding of encryption, IAM roles, and network security standards.

Why Join Us?
● Impact: You are not a cog in the machine; you are building the machine.
● Tech Stack: Work with the latest tools in the Cloud and Data world (Lakehouse, GKE).
● Culture: We value technical excellence, proactive problem-solving, and a “fail fast, learn
faster” mentality.
● Growth: We invest in your certifications and continuous learning. Ready to redefine how BI meets SRE? If you are a builder who loves solving the puzzle of high-scale data infrastructure, we want to meet you.

Apply now and let’s build the future of data infrastructure together!

About us:
We are a fast-growing product company seeking an experienced  Marketing Manager (part-time work) to lead marketing efforts for our mobile apps (iOS/Android). You will play a key role in shaping strategy, driving growth, and mentoring the team.

Responsibilities & Requirements:

• 3+ years of experience as a Marketing Manager in mobile products (iOS/Android).
• Strong understanding of the full mobile product development lifecycle.
• Develop and execute marketing strategies for mobile apps.
• Drive user acquisition, retention, and monetization.
• Plan and support new app launches, updates, and feature releases.
• Manage marketing budgets and optimize advertising campaigns.
• Analyze the market, competitors, campaign results, and key performance metrics.
• Run A/B tests and identify new growth opportunities.

• Collaborate with product, development, design, and analytics teams.

   

We offer:

• Part-time
• Competitive salary based on experience
• Paid sick leave and annual leave
• Fully remote work format
• Stable workload and long-term cooperation

About Our Client
 

Our client builds and operates GPU cloud infrastructure at the scale modern AI demands. They run dense accelerated-compute clusters on bare metal and Kubernetes, stitched together with high-performance Ethernet and InfiniBand fabrics, and deliver them to customers as reliable, secure, high-throughput platforms. They are building Cloud v2, their next-generation, clean-slate, Kubernetes-native GPU cloud, and scaling it across new data center sites. The infrastructure team sits at the center of that effort, building the systems that turn racks of hardware into a product customers depend on.
 

The role

We are hiring a Senior Observability Engineer to build the observability layer for Cloud v2. This role exists to close the single most damaging gap in our client’s current product: today their observability is reactive, so customers are their failure detector. Some of their worst incidents went undetected internally because they occurred below the layer they instrument (a corrupted forwarding entry, a flapping firewall sync process), and the customer reported the outage before their dashboards did. Cloud v2 is architected from day one against the industry’s Gold-tier bar for neocloud platforms (SemiAnalysis ClusterMAX), and proactive detection, where they see problems before the customer does, is the trust gap they are building this platform to fix.
 

You own the metrics, logs, alerting, dashboards, and detection stack that make that true. That means operator-facing observability that catches failures first and drives automated remediation, and tenant-facing observability that gives customers the usage, health, and status visibility a hyperscaler-grade cloud implies. This is the observability workstream the platform validates earliest, because detection is where the current product loses trust, and it maps directly to the ClusterMAX Monitoring and Reliability criteria.
 

This is a build-focused, hands-on senior IC role. You will spend your time engineering the telemetry pipelines, detection logic, dashboards, and alerting that turn raw signals from multi-vendor GPUs (AMD/NVIDIA), hosts, fabrics, and switches into problems we catch before customers feel them, and you will set the technical direction and standards for how we instrument the platform. You will partner closely with our client’s SRE, platform, network, and security engineers, who own the control-plane architecture, the fabric, and day-to-day operations; you own the observability that makes the whole platform legible and its failures visible.
 

What you’ll own

The OpenTelemetry foundation: own OpenTelemetry as the instrumentation standard the whole platform plugs into: the collector topology and pipelines, semantic conventions for metrics, logs, and traces, and consistent resource and tenant attribution across GPU, host, fabric, switch, and control-plane signals. Everything we instrument, internal and tenant-facing, lands on this common backbone so signals are portable, correlated, and not locked to any one backend.

Proactive detection: build the detection that fires before a customer reports, GPU failure-rate tracking, Xid detection, and the anomaly and threshold signals that feed the automated detect-drain-remediate loop, so mean time to detect stops being inverted and our client sees the problem first.

The metrics pipeline: own the metrics stack across GPU, CPU, network planes, thermal, and power (Prometheus and OpenTelemetry-based), including the DCGM profiling-metric suite (DCGM_FI_PROF_* for SM activity and tensor TFLOPs, plus PCIe AER, ECC, power and thermal, and NVLink and fabric throughput), with custom exporters and OpenTelemetry receivers where DCGM falls short.

Instrumenting below the layer we watch today: push instrumentation down into the sub-layers where our most damaging silent failures live (forwarding state, firewall and HA sync, fabric health), so the failure classes that used to reach us through the customer surface on our own dashboards instead.

Host and switch debug data: build reliable extraction of host and switch debug and telemetry data so responders have the signal they need without hand-collecting it during an incident.

Operator and tenant dashboards and alerting: build the operator dashboards and low-noise, actionable alerting the on-call team runs on, and a tenant-facing status page so customers are not our failure detector.

Tenant-scoped observability: deliver per-tenant usage and utilization visibility and per-tenant access to logs and metrics, cleanly isolated from internal ops telemetry, on a multi-tenant model where no tenant can see another’s data.

Proactive customer notifications: build automated, proactive maintenance and change notifications to affected tenants, replacing today’s manual and ad hoc comms.

Reliability and SLO instrumentation: build the telemetry behind the 99.9%+ node SLA measurement, the passive and active health-check battery, and MTTA and MTTR tracking, so reliability is measured, not asserted, and so the health automation has trustworthy signal to act on.

AI-leveraged observability: push our observability toward an AI-augmented model, agentic triage, anomaly detection, alert-noise reduction, and MCP-driven access to our operational telemetry, so a small team catches more, faster, than headcount alone would allow.

Technical direction and standards: set the instrumentation patterns, metric and label conventions, alerting standards, and SLO practice the rest of the platform adopts, and raise the bar through design review and mentorship.
 

What we’re looking for

Required

8+ years building production observability or monitoring systems at scale, ideally for cloud, hosting, or high-performance compute environments, with real platform-build experience (not solely operating dashboards someone else built).

Deep expertise with Prometheus and the metrics ecosystem: PromQL, exporters, recording and alerting rules, Alertmanager, and Grafana, used to build durable, reusable observability rather than one-off dashboards.

Hands-on experience designing and running OpenTelemetry as a foundational instrumentation layer: the Collector, receivers and exporters, semantic conventions, and vendor-neutral pipelines that multiple backends and teams plug into.

Experience running time-series at scale, including long-term and high-cardinality storage (Thanos, Mimir, Cortex, or VictoriaMetrics), and a real understanding of cardinality, retention, and query-performance tradeoffs.

A track record of building alerting that is actionable and low-noise, and of practicing SLO and error-budget-based reliability rather than alert on everything.

Strong programming skills in a real language (Python, Go, or similar) used to build maintainable exporters, collectors, and observability tooling, not just glue scripts.

Strong Linux systems fundamentals: you can reason about the OS, networking, storage, and the boot and provisioning path, and instrument at that level, not just at the application surface.

A track record of owning significant observability systems end to end and setting technical direction that other engineers adopt: defining standards and influencing architecture across a team.

A demonstrated bias toward building things right the first time: reproducible, code-defined observability and sound instrumentation design over short-term shortcuts.

Strong written communication: you document designs and decisions clearly, and you raise the team’s bar through design review and mentorship.
 

Strongly preferred

Multi-vendor GPU/HPC observability: DCGM & dcgm-exporter (NVIDIA) and RDC & AMD Device Metrics Exporter (AMD/ROCm); NVML and AMD SMI; Xid vs. amdgpu/RAS error reporting; DCGM_FI_PROF_* and ROCProfiler profiling metrics; GPU node health checks (DCGM diagnostics, AGFHC, ROCm Validation Suite).

Experience building multi-tenant, tenant-facing observability with per-tenant metric and log isolation.

Checkmk (our client runs parent and child sites today), and experience migrating or bridging a Checkmk estate into a modern metrics stack.

Network and fabric observability: switch telemetry, streaming telemetry (gNMI) and SNMP, BGP and fabric health, and RoCE Ethernet or InfiniBand/UFM fabric monitoring.

Log and trace pipelines and distributed tracing: Loki, Elastic, or Vector, and instrumenting traces across a distributed control plane.

Kubernetes observability: kube-state-metrics, cAdvisor, and GPU Operator metrics, in a multi-cluster environment.

Status-page and incident tooling, MTTA and MTTR instrumentation, and integration with an incident-response and paging workflow.

Building observability within a SOC 2, ISO 27001, or HIPAA compliance posture, including audit-log export.
 

How we work

Small, senior, high-trust teams. We hire people who can own and solve problems end to end and we give them the room to do it.

Code over clicks. The platform is defined, reviewed, and versioned. Manual changes are the exception and they get automated away.

Build it right. We invest in sound architecture and durable design so the platform scales cleanly instead of accumulating debt.

Customers are real. The platform exists to serve customer workloads, and we build to the reliability and self-service standard a hyperscaler-grade cloud implies.

We document. Designs, decisions, and architecture are written down so the team compounds knowledge instead of re-learning it.
 

AI as a force multiplier

We expect our engineers to use AI to move faster and operate at higher leverage, and we build our environment to make that the default rather than an afterthought. We maintain CLAUDE.md and AGENTS.md context files across our repositories, run MCP servers against our operational systems (Jira, NetBox, Checkmk), and use agentic coding tools such as Claude Code directly in our infrastructure and platform workflows.
 

For this role in particular, observability is one of the highest-leverage places to apply AI: anomaly detection, automated incident triage, alert-noise reduction, and AI-assisted root-cause analysis over the telemetry you build. You don’t need to be an AI expert, but you should be eager to fold these tools into how you design and operate observability, and to help us define what an AI-leveraged infrastructure team can do.

What success looks like
 

First 30 days

Ramped on the Cloud v2 architecture, the current observability stack (Prometheus, Checkmk parent and child sites, and the GPU and fabric telemetry), and the lab, and able to navigate the repos and design docs independently.

Shipped your first meaningful contribution to the metrics, alerting, or detection stack with the team’s review.

Aligned with SRE, platform, network, and security on where your work meets theirs and on the highest-value detection gaps to close first.
 

First 90 days

Owning a defined area of the v2 observability layer end to end, from design through delivery (for example the OpenTelemetry instrumentation foundation, the GPU and DCGM metrics pipeline, the alerting and SLO framework, or the tenant-facing dashboards and status page).

Delivered proactive detection for at least one failure class that the platform previously learned about from customers, so our client now detects it first.

Measurably reduced alert noise or improved mean time to detect for a meaningful part of the fleet.
 

First 12 months

The go-to engineer for the hardest observability and detection problems in Cloud v2, trusted across SRE, platform, network, and security, and setting the standards the team instruments by.

Designed and delivered a significant piece of the platform’s observability (proactive detection, tenant-facing observability, or reliability and SLO instrumentation) that raised the whole team’s leverage and moved the platform toward its Gold-grade Monitoring and Reliability bar.

Про нас

Ми — амбітна медіабаїнгова команда, яка спеціалізується на вертикалі Nutra та щодня масштабує рекламні кампанії на міжнародних ринках. Ми об'єднали сильних медіабаєрів, аналітиків, дизайнерів, розробників і технічних спеціалістів, щоб створити ефективну екосистему для стабільного масштабування та високих результатів.

Ми постійно тестуємо нові підходи, офери, креативи та GEO, масштабуємо успішні зв'язки й впроваджуємо сучасні інструменти автоматизації. Для нас важливі ініціативність, відповідальність і прагнення до розвитку. Ми створюємо умови, щоб кожен медіабаєр міг реалізувати свій потенціал, працювати з великими бюджетами та отримувати високий фінансовий результат.

Ваші обов'язки

• Запуск, оптимізація та масштабування рекламних кампаній у Facebook Ads.
• Пошук і тестування нових Nutra-оферів, зв'язок, креативів, аудиторій та GEO.
• Аналіз основних показників ефективності: CPA, ROI, ROAS, CR.
• Робота з трекерами, антидетект-браузерами, проксі та іншими професійними інструментами.
• Генерація нових гіпотез та постійна оптимізація рекламних кампаній.
• Аналіз якості та конверсії трафіку.
• Взаємодія з дизайнерами, аналітиками та технічною командою.
• Контроль виконання KPI та масштабування прибуткових зв'язок.

Наші очікування

• Досвід роботи Media Buyer у вертикалі Nutra.
• Впевнене володіння Facebook Ads Manager.
• Практичний досвід роботи з антидетект-браузерами, трекерами та рекламними акаунтами.
• Розуміння принципів тестування, оптимізації та масштабування рекламних кампаній.
• Досвід роботи з різними GEO та Nutra-оферами.
• Аналітичне мислення, відповідальність та орієнтація на результат.
• Готовність працювати з великими бюджетами та масштабувати успішні кампанії.
• Бажання постійно розвиватися та вдосконалювати свої навички.

Ми пропонуємо

• Конкурентну фіксовану ставку + високий відсоток від прибутку.
• Одну з найкращих інфраструктур для роботи з Nutra-трафіком.
• Великі бюджети для масштабування успішних кампаній.
• Власні інструменти, технічну підтримку та якісні витратні матеріали.
• Сильну команду професіоналів, готових ділитися досвідом.
• Гнучкий графік роботи без жорсткого контролю часу.
• Можливість працювати віддалено або в сучасному офісі.
• Кар'єрне зростання та професійний розвиток.
• Своєчасні виплати.
• Комфортну атмосферу, відкриту комунікацію та підтримку команди.

Ми — амбітна медіабаїнгова команда, яка спеціалізується на вертикалі Gambling та щодня масштабує рекламні кампанії на міжнародних ринках. Ми об'єднали сильних медіабаєрів, аналітиків, дизайнерів, розробників і технічних спеціалістів, щоб створити ефективну екосистему для досягнення максимальних результатів.

Ми постійно тестуємо нові підходи, масштабуємо успішні зв'язки та впроваджуємо сучасні інструменти автоматизації. Для нас важливі ініціативність, відповідальність і прагнення до розвитку. Ми створюємо всі умови, щоб кожен член команди міг реалізувати свій потенціал, працювати з великими бюджетами та досягати високих фінансових результатів.

Ваші обов'язки

• Запуск, оптимізація та масштабування рекламних кампаній у Facebook Ads.
• Пошук і тестування нових зв'язок, креативів, аудиторій та GEO.
• Аналіз основних показників ефективності (CPA, ROI, ROAS).
• Робота з трекерами, антидетект-браузерами, проксі та іншими професійними інструментами.
• Генерація нових гіпотез і постійна оптимізація рекламних кампаній.
• Взаємодія з дизайнерами, аналітиками та технічною командою.
• Контроль якості трафіку та виконання поставлених KPI.

Наші очікування

• Досвід роботи Media Buyer у вертикалі Gambling.
• Впевнене володіння Facebook Ads Manager.
• Практичний досвід роботи з антидетект-браузерами, трекерами та фарм-акаунтами.
• Розуміння принципів тестування та масштабування рекламних кампаній.
• Аналітичне мислення, відповідальність та орієнтація на результат.
• Бажання постійно розвиватися та вдосконалювати свої навички.

Ми пропонуємо

• Конкурентну фіксовану ставку + високий відсоток від прибутку.
• Одну з найкращих інфраструктур на ринку.
• Необмежені бюджети для масштабування успішних кампаній.
• Власні інструменти, технічну підтримку та якісні витратні матеріали.
• Сильну команду професіоналів, готових ділитися досвідом.
• Гнучкий графік роботи без жорсткого контролю часу.
• Можливість працювати віддалено або в сучасному офісі.
• Кар'єрне зростання, професійний розвиток та своєчасні виплати.
• Комфортну атмосферу, відкриту комунікацію та підтримку команди.