Jobs AI

You will join a small, high-trust Cyber Security Engineering team responsible for strengthening the security posture of a modern, globally distributed technology environment.

This is a hands-on engineering role focused on application security, container security, and AI security. You will build automated security controls, guardrails, and real-time visibility that make the secure path the easiest path for engineering teams.

You’ll work closely with platform engineering, cloud infrastructure, identity, technology assurance, and security leadership teams. The role offers significant ownership and the opportunity to influence not only technical controls, but also security standards and governance decisions across the organization.

This is not a role focused on manually reviewing individual applications. You’ll be expected to build automated, scalable security solutions that enforce standards at the point of deployment and provide clear visibility into security risks across running environments.

What we’re looking for:

We need a technically strong security engineer who understands that security and developer experience should work together.

The ideal candidate:

• thinks in terms of automation, scalability, and enforceable controls rather than manual reviews;
• has strong hands-on experience with Kubernetes and container security;
• understands application security, software supply chain risks, and secure development practices;
• enjoys building security tooling, observability, and policy-as-code solutions;
• is actively using AI-assisted development tools in their own engineering workflow;
• has practical or growing experience with AI and LLM security;
• can communicate complex technical findings clearly to senior technical and security stakeholders;
• is comfortable working in a small, collaborative, high-trust environment;
• approaches security friction as an engineering problem to solve.

Responsibilities:

• Design and deploy automated security controls for Kubernetes and application deployments.
• Implement admission controllers, policy-as-code, and automated security scanning.
• Define and enforce container security standards, including image scanning, runtime baselines, and registry governance.
• Manage software supply chain security, including dependency scanning, SBOMs, build-time and runtime analysis.
• Build application security observability and dashboards that provide real-time visibility into deployed and running systems.
• Develop automated guardrails that enable teams to use AI coding tools securely without requiring manual security review for every use case.
• Own security configuration and controls for AI platforms, including access controls, data flows, hardening, and protection against prompt injection and data exfiltration.
• Assess security risks associated with AI tools, MCP connectors, APIs, and agentic systems.
• Define security and behavioural baselines for agentic execution environments.
• Collaborate with security and engineering teams on container runtime telemetry and monitoring.
• Work with identity and cloud security teams on workload access, service identity, and secrets management.
• Curate and automate internal security tooling with a focus on reliability, security, and operational efficiency.
• Contribute to security standards, technical controls, and governance decisions.
• Communicate security findings and recommendations to senior stakeholders.

Requirements:

• Proven hands-on experience with Kubernetes and container security.
• Experience with container image scanning, admission control, runtime protection, and policy-as-code.
• Experience building automated security controls that can scale across complex environments.
• Strong understanding of application security fundamentals, including OWASP Top 10 and secure software development practices.
• Experience with software supply chain security and dependency management.
• Experience building security visibility through instrumentation, runtime analysis, monitoring, or operational dashboards.
• Experience with CI/CD security and automated security checks.
• Active experience using AI-assisted development tools such as Claude Code, GitHub Copilot, or equivalent.
• Practical or growing knowledge of AI/LLM security, including prompt injection, data exfiltration, model/API security, or agentic system controls.
• Strong analytical and problem-solving skills.
• Ability to communicate complex technical security topics clearly and concisely to senior stakeholders.
• Advanced English.

Nice to have:

• Experience with security tools such as Aikido, CrowdStrike, Bold Security, Nightfall, Zscaler, or Lakera Guard.
• Experience with MCP (Model Context Protocol), agentic frameworks, or AI platform administration.
• Experience in private equity, FinTech, financial services, or other environments where protection of sensitive information is critical.
• Experience measuring and optimizing the operational cost of security controls.
• Experience working with local or open-source LLMs for automation and security use cases.
• Experience with Datadog or similar observability platforms.
• Experience with SBOM tooling and software composition analysis.
• Experience with cloud security and workload identity.
• Experience working with policy-as-code frameworks.

Tools you’ll work with:

Kubernetes, CI/CD platforms, SBOM tooling, Aikido, Claude Enterprise, Claude Code, MCP, CoWork, DTEX, Datadog, and policy-as-code frameworks.

We are an IT services company based out of San Francisco, USA. ​​We build and acquire expert engineering teams to help our clients meet their business needs and solve their operational challenges.

We are looking for a Senior Software Engineer for long-term contract work to join one of our client’s Development Product Teams. This is a hands-on engineering role. You will write the code, review it, deploy it, and be on the hook when it misbehaves. There is no layer between you and production, and no layer between you and the people who depend on the platform.

This position may require working between the hours 12:00 PM to 8:00 PM Kyiv time. 

Tech Stack: 

• Backend: C# / .NET (ASP.NET Core Web API), Entity Framework, xUnit, REST APIs
• Azure: App Service and deployment slots, Azure SQL, Redis, Key Vault, Functions/WebJobs, Service Bus, Event Grid, Application Insights / Log Analytics, Azure DevOps pipelines
• Edge: Cloudflare (WAF, Workers, cache and redirect rules)
• Integrations: Salesforce (REST and SOAP APIs, OAuth, Connected Apps), OIDC-based member identity, learning and event platforms
• AI & Developer Tooling: GitHub Copilot, ChatGPT, Claude, or similar AI-assisted development tools

Requirements: 

• 8+ years building and running production C#/.NET web applications and APIs, including ownership of what you shipped.
• Strong, current Azure experience as a developer who operates their own environments: App Service and slots, Azure SQL, Key Vault, managed identities, and diagnosing problems from logs and metrics rather than guesses.
• Comfort in a small team with a wide surface area: you can pick up unfamiliar code, work without a spec, and ask the sharp question early.
• Must have experience applying AI within development. More detailed experience with AI-Native development and AIDLC preferred.

Would be Preferred:

• Azure DevOps (or comparable) pipelines — you have built and fixed CI/CD, not just pushed the button.
• Integration work against third-party SaaS APIs — OAuth flows, rate limits, sandbox data, and the failure modes that only appear in production.
• Salesforce platform integration experience (Connected Apps, client-credentials OAuth, staging test data).
• Automated testing as a habit, not a phase: unit, integration, and end-to-end, and the judgement to know which one a given risk deserves.
• Microsoft Azure certification — Azure Developer Associate (AZ-204) or a comparable Azure credential.

We’re looking for an AI Automation Engineer to build and launch an automated video production pipeline for Counter-Strike 2 content.

The goal is to automate the full workflow for YouTube Shorts, Instagram Reels, and TikTok — from content sourcing and AI processing to editing, voice-over, subtitles, publishing, and performance tracking.

Responsibilities

• Design and build an end-to-end video automation pipeline from scratch;
• Build complex n8n workflows with schedules, queues, conditions, parallel branches, retries, and error handling;
• Integrate LLMs and AI APIs such as OpenAI, Anthropic, and others;
• Integrate video generation, processing, and editing services via API;
• Automate AI avatars, lipsync, voice-over, dubbing, and character modifications;
• Automate video editing: different sources, scenes, hooks, subtitles, and voice-over;
• Set up scheduled publishing via YouTube Data API, Instagram Graph API, and other platform APIs;
• Work with OAuth, multiple accounts, API limits, and logging;
• Implement automated pre-publish checks: descriptions, hashtags, stop-lists, and AI-content labels;
• Build an operator dashboard for content calendar, queues, errors, providers, and content types;
• Collect performance metrics and optimize content distribution based on results;
• Monitor, troubleshoot, and scale the pipeline to new platforms and channels;
• Maintain technical documentation: README, ARCHITECTURE, RUNBOOK.

Requirements

• Hands-on experience building automation workflows / pipelines from scratch;
• Strong n8n experience with complex production workflows;
• Knowledge of Python or JavaScript for custom scripts;
• Experience with REST APIs, Webhooks, and OAuth;
• Experience integrating LLMs / AI APIs such as OpenAI or Anthropic;
• Experience with video generation, processing, or editing APIs;
• Experience with social media publishing APIs such as YouTube API / Instagram Graph API;
• Ability to independently break down a task, choose the right tools, build the solution, and bring it to stable production;
• English sufficient for reading technical documentation.

Nice to have

• Experience with AI content generation pipelines;
• Experience with FFmpeg or similar video-processing tools;
• Experience with AI avatars, lipsync, TTS/STT, voice cloning, or dubbing;
• Experience automating TikTok, Reels, or YouTube Shorts;
• Experience with Zapier, Make (Integromat), or similar automation tools;
• Understanding of monitoring, logging, queues, and fault-tolerant workflows.

What We Value

We’re looking for someone who can own the entire automation flow — from architecture and tool selection to MVP, production launch, optimization, and scaling.

We value autonomy, ownership, and a result-oriented mindset.

And if you play CS2 / CS, that’s an extra bonus — we also run internal CS2 tournaments 🎮

We are looking for an AI-First Golang Team Lead for one of our product engineering pods: a hands-on engineer who uses AI to ship fast and acts as the face of their pod towards clients and leadership.

⚠️IMPORTANT: This is not a traditional coding role. You’ll use Claude Code and other AI tools to 10x your output, always thinking about how the product or feature you are working on benefits the user. Also: we have no QA team, you OWN the quality of what you ship!

🧭About this role: every engineer on the team already owns their work end-to-end (IC + DRI). Everyone in the pod is, in effect, their own architect and lead developer. So this role is not about being the strongest techie in the room or telling people how to build.

A Team Lead is the spokesperson, coordinator, and facilitator for their pod, internally with product, design, and leadership, and externally with clients. You come from the management path, not the deep-specialist path: you have seen a lot as a developer and have consciously decided that enabling a team, working with clients and driving product outcomes is what energizes you now, not coding all day.

You remain a hands-on engineer. Expect roughly 30-40% of your week on coordination, client and product work, and the rest as an individual contributor. This is not an HR-style people-management role: no performance reviews, no career coaching. As we scale, light one-on-ones and check-ins may become part of it, but the job is coordination and delivery, not administration.

🧑 💻 What you’ll actually do:

• Be the spokesperson for your pod, internally with product, design, and leadership, and externally with clients and partners.
• Coordinate work across the pod: break initiatives into chunks, sequence them, surface blockers, and facilitate hand-offs (lightweight project management; we deliberately have no project managers).
• Gather client requirements first-hand and funnel them straight into the pod so nothing gets lost in translation.
• Represent your pod in product planning sessions and bring a strong product-driven point of view to scoping and trade-offs.
• Help pod members with product decisions and prioritization, enabling engineers who may be technically stronger than you.
• Contribute hands-on as an engineer: own features end-to-end, use Claude Code to generate Golang backend code, review AI output for quality and architectural fit.
• Join client meetings to align on requirements, report on delivery, and keep the relationship professional and calm.

📚 Our stack:

• Backend: Go monorepo (no framework, 3+ services).
• Hosting: PaaS-managed containers; local setup fully mirrors production via Docker Compose.
• Tools: Jaeger tracing, Betterstack (Logging, Alerting), Redis Asynq queue.
• Databases: PostgreSQL, Redis.
• AI tooling: Claude Code (mandatory).

🚢 Products you will lead a pod on:

• An AI search & recommendation engine for major travel enterprises: heavy client integration work (SSO, security reviews, GDS integrations) with demanding enterprise customers.
• A content enrichment API: high-scale, data- and AI-focused backend work.
• Partner and supplier integrations, data ingestion pipelines, LLM providers.

✅ You must have:

• 2-3+ years of technical leadership experience leading a team, squad, pod, or similar unit (a hard must; think team lead or early-stage engineering manager).
• A developer’s background (minimum 5 years): you have seen production reality with your own hands before moving towards leading people.
• A genuinely product-driven mindset: you think about user value and business outcomes before implementation.
• Comfort facilitating and coordinating a pod without relying on formal authority.
• Willingness and ability to take part in client meetings and act as the external face of your pod.
• Excellent spoken and written English for planning sessions, stakeholder updates, and client conversations.
• Ownership mentality with a strive for elegantly simple, high-quality solutions; you test your own work thoroughly since we have no QA team.
• Proven experience using Claude Code; share specific examples.
• Solid Golang experience; you’ll review AI’s code, and you must understand how it works.
• Ability to do on-call once in a while to help maintain our platform’s reliability & uptime.
• ⚠️ European or African timezones (±3 hours from CET).
• Available full-time (40 hours/week).

❤️ You are a great fit if you:

• Made the classic developer’s fork-in-the-road decision: lifelong engineer or leading people, and chose people, clients, and product.
• Are energized by product planning sessions and have opinions about what the pod should build next, not just how.
• Are comfortable being the face of your pod, in internal planning rooms and on calls with enterprise clients.
• Enjoy enabling engineers who are technically stronger than you.
• Ship fast but always verify it actually works; think “how can AI build this?” as your first instinct.
• Get frustrated when development takes weeks instead of days.

‼️Things to consider before applying that won’t be a match:

• This would be your first leadership role.
• You see the lead as the chief architect who makes the technical decisions for the team.
• You are looking for an HR-focused people-management role built around performance reviews and career coaching.
• You want to lead a team without staying hands-on in the codebase.
• You would rather not take part in client meetings or stakeholder-facing conversations.
• You prefer to focus on execution and leave product planning to others.
• You rely on formal authority to get a team moving.
• You have never used Claude Code or similar AI coding tools.
• You are outside European/African timezones.

AI courses for business people — from beginner to advanced — in English.

Duties

• Write lesson scripts that are clear, practical and enjoyable to read — no theory for theory's sake.
• Create the visuals: diagrams, AI-generated illustrations, annotated screenshots.
• Script and produce videos: click-by-click screen tutorials and narrated lesson videos (HeyGen, Synthesia or similar).
• Design practice assignments, self-check questions and a capstone project for each course.
• Test every prompt and tool step before it ships; keep content 100% original and free of unsourced statistics.
• Revise quickly on founder feedback.

Requirements: daily user of ChatGPT, Claude, Gemini and image tools; native-level English; portfolio with at least one course or five lessons and one video you produced yourself.

Terms: paid per module, first module is a paid pilot, start immediately.

Lime Vizio
Industry: High-Volume E-commerce (US & Canada)
Location: Remote
Schedule: Full-time, Los Angeles business hours(PST/PT)
Reports to: CEO & Founders

About the role

We are looking for a hands-on COO who builds businesses—not just manages them.

You'll own company operations, profitability, organizational effectiveness, and AI-driven transformation.

This role combines executive leadership with deep operational thinking. You'll work directly with the CEO to redesign systems, improve unit economics, develop leaders, and build an organization that scales without unnecessary complexity.

What You'll Own

• End-to-end company operations 
• EBITDA and operational profitability 
• AI & automation roadmap 
• Leadership performance and accountability 
• KPI framework and operational dashboards 
• Cross-functional execution 
• Organizational design and operational scalability 

Key Responsibilities

• Improve EBITDA, gross profit, and unit economics. 
• Reduce labor cost, refunds, cancellations, and operational waste. 
• Redesign and simplify business processes before automating them. 
• Lead AI and automation initiatives that deliver measurable business value. 
• Build scalable systems, KPIs, ownership, and operational standards. 
• Develop high-performing department leaders. 
• Improve fulfillment reliability, customer experience, and operational efficiency. 
• Partner with Product and Engineering to solve business problems through technology. 
• Personally investigate high-impact operational challenges and lead transformation initiatives. 
   

What Success Looks Like

You'll be responsible for measurable improvements in:

• EBITDA  
• Gross Profit 
• Profit per Order 
• Labor Cost per Order 
• Refund & Cancellation Rates 
• Fulfillment Performance 
• SLA Achievement 
• Customer Satisfaction 
• AI Automation Results 
• Leadership Effectiveness 
   

Requirements

• 10+ years in Operations, Business Transformation, or Executive Leadership. 
• Experience leading organizations of 100+ employees. 
• Strong background in high-volume e-commerce (required). 
• Proven success improving profitability and scaling operations. 
• Experience redesigning operational systems—not just managing teams. 
• Strong understanding of unit economics and operational finance. 
• Experience leading automation, digital transformation, or AI initiatives. 
• Experience working closely with Product, Engineering, Data, and Finance. 
• Experience managing remote international teams. 
• Excellent English (B2+). 
   

Nice to Have

• Marketplace or aggregator businesses 
• Logistics or fulfillment operations 
• Contact centers 
• BI & operational analytics 
• CRM / ERP / workflow automation 
• Lean or Six Sigma 

This Role Is Not for Someone Who

• Maintains operations instead of improving them. 
• Measures activity instead of business outcomes. 
• Solves problems by adding headcount. 
• Automates broken processes instead of redesigning them. 
• Avoids difficult organizational decisions. 
• Relies on meetings instead of execution. 
• Isn't comfortable being accountable for financial results. 
   

Why Join Lime Vizio

• Full ownership of company operations. 
• Direct partnership with the CEO and founders. 
• High-impact executive role. 
• Fast decision-making with minimal bureaucracy. 
• Opportunity to build one of the most operationally efficient AI-native e-commerce companies. 

About Lime Vizio

Lime Vizio is a multi-brand e-commerce company serving customers across the United States and Canada.

We process thousands of customer orders daily through customer support, sales, fulfillment partners, finance operations, proprietary technology, and AI-powered systems.

We're building an AI-native company where technology performs routine work while people focus on leadership, customer experience, and business growth.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv — you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

Turn your curiosity for automation and AI into a technology career. 

We are looking for self-driven professionals from Assurance who have demonstrated a passion for improving the way work gets done through Python, automation, data analytics, Copilot, or Generative AI. Whether you have built scripts, automated repetitive tasks, experimented with AI tools, or simply enjoy exploring new technologies, this role offers an opportunity to transform that passion into a full-time technology career. 

As a Junior AI Engineer, you will learn how to design and develop scalable AI-powered solutions while combining your audit and business knowledge with modern engineering practices. Working alongside experienced AI engineers, you will gain hands-on experience with Python, Generative AI, cloud platforms, intelligent automation, and enterprise AI solutions. 

This is a career opportunity for professionals who want to evolve from being consumers of technology into creators of technology, helping shape how AI is used across PwC and for our clients. While previous AI engineering experience is not required, a genuine interest in technology, continuous learning, and hands-on experimentation is essential. 

Key Responsibilities 

AI Solution Development:

• Develop AI and automation solutions using Python. 
• Build and maintain integrations with LLM APIs and AI services.
• Support implementation of RAG-based applications.
• Assist in developing prompt engineering strategies and reusable AI components.
• Participate in testing, debugging, and improving AI solutions. 

Engineering Excellence:

• Write clean, maintainable, and well-documented code.
• Participate in code reviews and technical discussions.
• Create and maintain REST APIs and backend services.
• Support CI/CD pipelines and deployment activities.
• Follow secure coding and software engineering best practices. 

Data & AI Operations:

• Prepare and process structured and unstructured data.
• Assist with document processing, OCR, chunking, and embedding pipelines.
• Work with SQL and vector databases.
• Monitor AI solution performance and troubleshoot production issues. 

Learning & Innovation: 

• Continuously learn emerging AI technologies and frameworks.
• Contribute to internal proof-of-concepts and AI adoption initiatives.
• Share knowledge with the broader AI engineering community. 

Required Qualifications 

Technical Skills: 

• 1–3 years of experience in software development or automation.
• Good Python programming skills.
• Understanding of object-oriented programming and software engineering principles.
• Experience working with APIs and JSON data structures.
• Basic knowledge of Git and version control workflows.
• Understanding of relational databases and SQL.
• Familiariaty with cloud concepts (Azure preferred).
• Interest in Artificial Intelligence and Generative AI technologies. 

AI Knowledge:

• Experience using AI IDEs (Cursor/Copilot/Claude/and so on) during daily work.
• Basic understanding of:  Large Language Models (LLMs), Prompt Engineering, Embeddings, RAG concepts, Vector search fundamentals.

Nice-to-Have Skills

• LangChain, LangGraph, CrewAI, Semantic Kernel 
• Azure AI services
• Azure AI Search
• Azure Document Intelligence
• Azure AI Foundry
• FastAPI or Flask
• Docker containers
• Kubernetes basics
• Vector databases (Qdrant, pg_vector, Azure AI Search)
• Async Python programming
• Event-driven architectures and messaging systems
• Pandas and data processing libraries
• GitHub Actions or Azure DevOps pipelines 

Policy statements:
www.pwc.com/ua/uk/about/privacy.html

Location: Remote
Compensation: $4,000–6,000 fixed + performance-based KPI bonus
Industry: AI Companion / Adult / NSFW / Subscription Apps

We are looking for a CMO / Head of Performance to take full ownership of performance marketing and growth for two international AI Companion products, including an Adult / NSFW AI Companion (AI Girlfriend) product.

This is not a role for someone focused on a single acquisition channel. We are looking for a senior growth leader with direct experience in Adult / NSFW, AI Companion, AI Girlfriend, Dating, or closely related high-risk subscription products, who understands how to scale paid acquisition under strict advertising restrictions.
 

Key Responsibilities

• Build and execute the overall performance & growth strategy for AI Companion products.
• Scale acquisition across Meta, Google, TikTok, Adult Ad Networks and Affiliate channels.
• Own the full web funnel: landing pages → onboarding → paywall → subscription → rebills/retention.
• Manage performance economics: CAC, CPA, ROAS, LTV, ROI, Payback, Retention and Conversion Rate.
• Build scalable acquisition strategies specifically for Adult / NSFW AI Companion traffic.
• Develop and maintain sustainable high-risk advertising infrastructure, including account management, moderation challenges, bans, backups and recovery processes.
• Build and manage the performance team: Media Buyers, Creative specialists and other growth roles.
• Own the creative testing strategy and continuously generate new acquisition hypotheses.
• Work closely with Product on onboarding, monetization, retention and LTV improvements.
• Build processes, reporting and analytics required to scale acquisition globally.
   

Must-Have Experience

• 4+ years in Performance Marketing / Growth, with experience in a senior or leadership role.
• Direct experience with Adult / NSFW / AI Companion / AI Girlfriend / Dating or similar high-risk subscription products.
• Strong understanding of Adult traffic acquisition and the limitations of mainstream advertising platforms.
• Hands-on experience scaling web-based subscription funnels.
• Strong knowledge of subscription unit economics: CAC, LTV, ROAS, Payback, Retention, rebills.
• Experience with multiple acquisition channels — ideally Meta + Google/TikTok + Adult Networks and/or Affiliates.
• Proven experience dealing with high-risk moderation, account restrictions and advertising infrastructure.
• Experience managing and scaling significant paid acquisition budgets; ideally $1M+ monthly.
• Experience building a performance team and processes from scratch.
• Strong analytical mindset combined with hands-on performance expertise.
   

Ideal Background

The strongest candidates will come from products in:

AI Companion / AI Girlfriend / NSFW AI → Adult Subscription → Dating Subscription → Creator Monetization / Adult Tech.

Experience exclusively in iGaming/Gambling without Adult, Dating or subscription-product exposure will be considered less relevant for this role.
 

What We Offer

• Full ownership of the performance and growth function.
• Opportunity to build your own team and acquisition processes.
• Two active international AI products with existing traffic.
• High level of autonomy and direct influence on product growth and monetization.
• Fully remote format.
• $4,000–6,000 fixed + KPI-based bonus, with final compensation discussed individually based on experience.

Sovrano AI, SL is a Barcelona company selling verified European expert capacity to frontier AI labs, robotics companies and enterprise AI teams. A network of 400,000 or more professionals, 100 or more partner universities across Europe, EFMD certification, 23 languages, a funding round led by b2venture, and a proprietary benchmark in EuroExec.

The job

You build the interview agent: a real time voice system that talks to candidates, listens, and holds a conversation that has to feel right on the first attempt. Speech to text on the way in, an LLM in the middle, text to speech on the way out, and a latency budget measured in hundreds of milliseconds. Someone interrupts halfway through a sentence and the agent handles it the way a person would. A model stalls, and the failure sounds like a pause rather than a crash.

Real time voice is unforgiving in a way that ordinary product work is not. There is no loading spinner. It either feels like a conversation or it does not, and the difference is measured in milliseconds you have to go and find.

The interface is as much of the product as the model behind it. You lead on the UI, and you care how it feels rather than only whether it works.
 

The stack

The agent is Python on LiveKit, with streaming speech to text and streaming text to speech either side of an LLM. The interface and the wider platform are Node.js, TypeScript and React, on PostgreSQL and Google Cloud. You work across both halves.
 

You own

• The interview agent end to end: the real time voice pipeline, the model integration, and the prompt and evaluation loop behind it
• Latency, interruption, endpointing, turn taking, and what happens when a model or a network stalls mid sentence
• The candidate facing interface, from interaction design through to shipped frontend
• Model quality, measured rather than asserted. Eval datasets, regression testing on prompt changes, and knowing whether a change made the conversation better or only different
• Integrations that bring the agent, its output and its evidence into the rest of the platform

The experience we require
 

• Five or more years building production software, full stack, with strong frontend depth in TypeScript and React
• Real time audio shipped to production. Streaming speech to text and text to speech, WebRTC or an equivalent transport, and the work that comes with them: voice activity detection, endpointing, turn taking and barge in
• LLM APIs in production. Streaming, tool calling, structured output, first token latency, cost, and what the product does when the model answers wrongly in front of a user
• You measure latency rather than estimate it. A p50 and a p95 you can quote per stage of the pipeline, and tracing good enough to say which hop is the expensive one
• Genuine UI and UX judgement. You take a rough idea to a designed, shipped interface and can explain the choices
• AI native. You already work with AI tools daily and build what you need without being shown how
• English at B2 or above
   

Also worth having

• LiveKit, or another real time agent framework run in production
• A view on the providers at each stage and why: Deepgram, AssemblyAI or Whisper for speech to text, ElevenLabs or Cartesia for speech out
• Speech to speech models, OpenAI Realtime or Gemini Live, and a position on when collapsing the pipeline is worth the control you give up
• Async Python and FastAPI
• Evaluation tooling: Langfuse, LangSmith, or something you built yourself
• Voice treated as personal data: redaction, retention and access control

Sovrano AI, SL is a Barcelona company selling verified European expert capacity to frontier AI labs, robotics companies and enterprise AI teams. A network of 400,000 or more professionals, 100 or more partner universities across Europe, EFMD certification, 23 languages, a funding round led by b2venture, and a proprietary benchmark in EuroExec.
 

The job

You are the engineering lead on the platform, working alongside the CTO every day. Platform architecture, scaling, infrastructure and data are yours. When a query gets slow, when a service will not hold the next order of magnitude, when a feature needs to be designed before it can be built, that is your call to make.
 

This is roughly 70 percent building and 30 percent raising the standard of everyone else's work: reviewing pull requests, setting the code quality bar, unblocking teammates and making decisions that stop being reversible three months later.
 

You own

• Platform architecture and the scaling path, from schema and query performance to infrastructure and cost
• Delivery of the harder platform features end to end, from design through production
• Code quality across the codebase: review standards, testing, what ships and what does not
• Technical decisions made with the CTO, and the ones made on your own when the CTO is not in the room
• The engineers around you getting better, through review, pairing and design conversations
   

The experience we require

• Seven or more years building production software, with real time spent on systems that grew past their first architecture
• Depth in relational data: schema design, query optimisation, and diagnosing performance from first principles rather than by guessing
• Cloud infrastructure and CI/CD owned in production, not consumed as a service someone else runs
• A track record of raising other engineers' work through code review and design feedback
• AI native. You already work with AI coding tools daily and build the tooling you need without being shown how
• English at B2 or above
   

Also worth having

• Experience in an AI or data platform company
• Time as a founding or first senior engineer somewhere
• Comfort moving across the stack when the work demands it

We are looking for a Legal Counsel to support a broad range of legal matters, with a primary focus on commercial contracts with clients and vendors. 

The role also covers intellectual property, corporate matters, compliance, privacy and other day-to-day legal issues across an international technology business. 

Responsibilities 

• Draft, review and negotiate wide range of contracts, including MSAs, SOWs, NDAs, DPAs, software, SaaS, licensing and vendor agreements. 
• Independently manage contract negotiations with clients, vendors and external counsel. 
• Identify legal and commercial risks and provide practical solutions and fallback positions. 
• Advise internal teams on legal matters arising in different jurisdictions, with a focus on the US and Europe. 
• Support IP-related matters, including software ownership, licensing, copyright and trademarks. 
• Support corporate, compliance, privacy and other legal matters as needed. 
• Conduct legal research and prepare clear, concise legal advice. 

Requirements 

• Master’s degree in Law. 
• 3+ years of relevant legal experience, preferably in an IT or technology company. 
• Strong experience drafting and negotiating commercial and technology contracts governed by US law and/or English law. 
• Good understanding of key technology-contract issues, including liability, indemnities, IP, data protection, information security and licensing. 
• Advanced English and Ukrainian. 
• Practical experience using generative AI tools in legal work. 

Nice to Have 

• Understanding of the US tax system. 
• Experience in the IT services, software development or outsourcing industry. 
• Experience with privacy, cybersecurity or AI-related legal matters. 
• Experience with information security and privacy frameworks or assurance standards, including ISO 27001, ISO 27701, SOC 2 or NIST frameworks. 
• Experience implementing or building legal-tech or automation tools, including AI-assisted development or vibe coding. 

What we offer   

• Continuous learning and career growth opportunities 
• Professional training and English/Spanish language classes   
• Comprehensive medical insurance 
• Mental health support 
• Specialized benefits program with compensation for fitness activities, hobbies, pet care, and more 
• Flexible working hours 
• Inclusive and supportive culture 

We are looking for a Middle AI/ML Engineer to develop computer vision and language-model capabilities for digital accessibility solutions. You will work on production-ready AI systems that help make websites and applications more usable for people of all abilities, combining classical computer vision, YOLO-based models, LLM integrations, embedding pipelines, vector search, and RAG APIs.
 

Required for this role

• 3+ years of experience in machine learning or AI engineering, with a focus on deploying models to production
• Strong knowledge of computer vision, including classical algorithms, object detection, and classification
• Hands-on experience with YOLO models for classification and object detection
• Proficiency in Python and common ML libraries such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face Transformers
• Experience working with LLMs, API integrations, embedding pipelines, vector databases, and RAG
• Strong back-end engineering skills, including API design, cloud service integration, and infrastructure supporting ML workflows
• Experience building and maintaining scalable ML infrastructure and data pipelines using tools such as AWS Glue, Athena, Spark, or similar
• Strong understanding of the ML model lifecycle, including training, evaluation, deployment, monitoring, and continuous improvement
• Familiarity with HTML, CSS, and JavaScript, together with an interest in digital accessibility
• Strong communication skills and the ability to explain complex ML concepts to technical and non-technical audiences
   

Your responsibilities

• Develop and improve computer vision solutions using classical algorithms and YOLO-based classification and object detection models
• Fine-tune LLMs and build embedding pipelines for production use cases
• Implement and validate vector search using vector databases
• Develop RAG modules and APIs, and integrate AI capabilities with existing systems
• Process and collect data for AI systems, building and maintaining pipelines for developing and deploying algorithms at scale
• Research current approaches in AI/ML and apply relevant findings to digital accessibility challenges
• Design, evaluate, and iteratively improve algorithms using rigorous statistical and domain-relevant metrics
• Contribute to technical documentation, code reviews, team planning, demos, presentations, and cross-functional collaboration

What you get
Your time off

• 18 paid vacation days and 10 paid sick days annually
• 10 Ukrainian public holidays
• Maternity and paternity leaves
• Marriage and Parenthood Package
• Additional leave for major life events
• Sabbatical leave opportunities
   

Learning & growth

• Sombra University workshops and internal learning programs
• Tech Communities and knowledge sharing sessions
• Language courses and workshops
• Mentorship opportunities
   

Health & well-being

• Sports compensation or health insurance coverage
• Participation in races and marathons
• Corporate doctor (telemedicine)
• Well-being initiatives and workshops
   

And even more

• Company-provided technical equipment
• PE administration and tax support
• Internal referral program
• IT Club loyalty program
• Company events and volunteering initiatives

Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the role:
We are looking for an ML Engineer / Applied Scientist to join a multidisciplinary team working on a network intelligence and reliability project for a distributed wireless sensor network.
The role focuses on evaluating the feasibility and potential value of machine learning and advanced analytics for network-state understanding, degradation prediction, capacity forecasting, decision support and predictive maintenance.
You will work with real-world network telemetry, historical operational data, simulator-generated data and controlled field experiments.

Responsibilities:
ML & Data feasibility
- Assess the availability and quality of historical data for ML use cases
- Analyze data coverage, class/event distribution, temporal coverage and labeling quality
- Identify data gaps and determine whether additional instrumentation or data collection is required
- Evaluate whether the available data contains sufficient signal for predictive or classification tasks
- Define appropriate training, validation and test strategies for temporal and network data
- Avoid data leakage and ensure that evaluation reflects realistic deployment conditions
Network-state analytics
- Work with the Network Architect and Data Engineer to define an analysis-ready representation of network state
- Analyze network states based on variables such as: topology, node/link status, routing, RSSI/SNR, packet loss, latency, traffic/load, battery state, device availability
- Develop analytical and ML approaches for identifying healthy, degraded, constrained or unstable network states
- Investigate temporal patterns and transitions between network states
Baseline development
- Establish reproducible statistical and deterministic baselines
- Define appropriate evaluation metrics for each hypothesis
- Compare candidate ML models against simple baselines
- Quantify whether ML provides meaningful improvement over existing approaches
- Analyze trade-offs between accuracy, complexity, interpretability and implementation requirements
Simulator-based experiments
- Work with the Network/Embedded Engineer to use the existing network simulator for controlled experiments
- Analyze simulator-generated datasets
- Compare simulated and real-world data distributions
- Assess whether synthetic data can safely be used for model development and evaluation
- Support scenario generation and experiment design
- Evaluate whether simulator results generalize to observed real-world network behavior
- Help identify simulator calibration requirements

Requirements:
- 4+ years of professional experience in Machine Learning, Applied Data Science, Data Science Engineering or a related field
- Strong Python skills and hands-on experience with ML/data science workflows
- Strong understanding of: supervised and unsupervised learning; classification; regression; time-series analysis; anomaly detection; forecasting; model evaluation.
- Experience working with temporal and event-based datasets
- Strong understanding of data leakage, train/validation/test splitting and evaluation methodology
- Experience building reproducible ML experiments
- Strong statistical fundamentals
- Experience establishing and evaluating non-ML baselines
- Ability to work with imperfect, noisy and incomplete real-world data
- Ability to translate a technical/business hypothesis into a measurable ML experiment
- Ability to communicate model results, limitations and uncertainty to technical and non-technical stakeholders

Nice to have:
- Network / Telemetry / IoT
- Experience working with data generated by: wireless networks, IoT devices, sensor networks, telecommunications systems, distributed infrastructure, industrial systems, robotics, edge devices
- Experience with network telemetry such as: RSSI, SNR, packet loss, latency, link quality, routing, topology, network load, node availability, battery telemetry
- Graph & Network analytics
- Simulation & Synthetic data
- Forecasting & Reliability
- Experience with: degradation prediction, reliability modeling, predictive maintenance, capacity forecasting, anomaly detection, failure prediction, survival/lifecycle analysis
- Experience in telecommunications, IoT, industrial systems, robotics, defense or other physical-system domains would be a strong advantage.

Technical Skills:
Required
- Python
- NumPy
- Pandas
- scikit-learn
- SQL
- Git
- Jupyter / equivalent experimentation environment
Preferred
- PyTorch
- XGBoost / LightGBM
- Time-series libraries
- NetworkX
- MLflow or similar experiment tracking
- PyArrow / Parquet
- PostgreSQL / TimescaleDB or similar
- Cloud data/ML services

We are looking for a Senior AI / Machine Learning Engineer with a strong software engineering and backend development background.

Full-time | Remote | Long-term engagment

Start: ASAP

Candidate location: EU

This is a hands-on engineering role combining Machine Learning, LLMs, backend development, and MLOps. We are looking for someone who can take an AI/ML use case, build the required solution in Python, integrate it with existing services and workflows, and make sure it can be run, tested, and maintained in a production environment.

The ideal candidate has strong experience with Python and backend development, a solid understanding of Machine Learning, and practical experience working with LLM-based solutions. Experience with AWS is required, while knowledge of Docker, Kubernetes, and MLOps is important for working effectively with the existing engineering and platform teams.

Our current focus is increasingly moving towards LLM-powered solutions. We are particularly interested in engineers who have practical experience integrating LLMs into real applications and business workflows. Experience with technologies such as OpenAI, AWS Bedrock, or Google Gemini is highly relevant, as well as experience with RAG, embeddings, model adaptation, or fine-tuning.

At the same time, this is not a research-focused or prompt-engineering role. We need someone with strong engineering skills who can build the backend and internal services around AI capabilities. Experience with APIs, databases, asynchronous processing, authentication/authorization, and writing maintainable production code is important.

You should also have a good understanding of MLOps and the ML lifecycle, including how models and AI services are developed, tested, deployed, monitored, and maintained. Hands-on experience with Docker and basic Kubernetes knowledge is expected.

Deep DevOps expertise is not required. Our Application Platform Team is responsible for most of the infrastructure and production deployment. However, you should be comfortable working with cloud-based environments, understand the principles behind MLOps, and be able to independently run and test your solution locally using the appropriate development and containerization tools.

Experience with AWS is essential. Experience with services such as SageMaker is useful, particularly for traditional ML use cases, although the main focus of the team is now shifting towards LLM-based applications.

Experience building AI agents is not a requirement. What matters most is practical experience using LLMs as part of existing applications, internal services, and business processes.

Key requirements

Strong Python and software engineering skills

Significant backend development experience

Experience building APIs and internal services

Solid understanding of Machine Learning and ML model lifecycle

Practical experience with LLMs / Generative AI

Experience integrating LLMs into applications and workflows

Strong AWS experience

Understanding of MLOps

Experience with Docker and basic Kubernetes

Experience working with databases

Understanding of asynchronous programming and concurrency

Experience with authentication and authorization

Ability to run, deploy, and test solutions locally

Experience with OpenAI, AWS Bedrock, or Google Gemini

RAG and vector search

Embeddings

LLM evaluation and optimization

Fine-tuning / adapting foundation models

LangChain or LangGraph

MLflow, Kubeflow, SageMaker

Kafka, Redis, or similar distributed systems technologies

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.
 

     You'll be a great fit if you have:

•  Strong Python Experience (2 year +);
• Experience with LLM , Diffusion models;
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;
• Strong experience in statistics;

• Bachelor's degree in Computer Science or a related field.
   

  What you'll do:

• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications.
   

     We ensure your growth with:

• Competitive salary fixed in USD;
• Flexible working schedule and fully remote work format;
• Paid vacation days and sick leave days ;
• Personal and professional development opportunities;
• Participation in building innovative projects from scratch using modern technologies;
• Team-building activities and corporate events;
• English classes and educational events.