Jobs at Djinni

We are looking for an Anti-Fraud Manager to protect our platform from fraudulent activity while ensuring a seamless experience for legitimate players. You will be responsible for monitoring suspicious behavior, investigating fraud cases, minimizing financial risks, and continuously improving fraud prevention processes.

The ideal candidate has hands-on experience in iGaming, understands common fraud schemes, payment abuse, bonus abuse, multi-accounting, and account takeovers, and is comfortable making data-driven decisions in a fast-paced environment.

Key Responsibilities:
 

• Monitor player activity and payment transactions to identify suspicious behavior
• Investigate fraud cases, including bonus abuse, multi-accounting, payment fraud, chargebacks, account takeovers, and affiliate fraud
• Make decisions regarding account verification, restrictions, suspensions, or closures
• Collaborate with Payments, Customer Support, VIP, CRM, and Product teams to resolve fraud-related issues
• Analyze fraud trends and recommend improvements to fraud prevention processes
• Monitor key fraud KPIs and prepare regular reports
• Participate in configuring fraud rules, limits, and risk scenarios
• Work closely with payment providers regarding fraud-related cases and chargebacks
• Maintain fraud documentation and internal procedures

Requirements:
 

• 2+ years of experience in Anti-Fraud, Risk Operations, Fraud Prevention, or Payments within iGaming
• Strong understanding of common fraud schemes in online gambling
• Understanding of KYC and AML procedures
• Experience configuring fraud detection rules
• Familiarity with responsible gaming policies
• Experience investigating suspicious transactions and player activity
• Understanding of payment methods, transaction flows, chargebacks, and risk management
• Strong analytical skills with the ability to interpret large volumes of data
• Experience working with fraud monitoring tools and back-office platforms
• Ability to make independent decisions based on risk assessment
• Intermediate English or higher

Brocoders is an Estonian software development company. Since 2014, we’ve built SaaS and AI products for clients across Europe and North America.

You’d join a small marketing team reporting to the Marketing Manager. Small team means your work is visible, and you’ll see what it moves.

Why this role exists

We produce material most companies our size cannot, and we are not getting it read.

Our CTO built a system that mines what people in an industry actually say to each other. For field service, it currently holds a database drawn from 3,900 business owners and technicians across more than 1,000 discussions and 13,000 comments, and it turns that into quarterly research: real prices people quote each other, the arguments they are having, what they are worried about. Numbers that do not exist anywhere else because nobody else collected them.

The first report is finished and unread.

It is not the only thing sitting unused. We have 29 published case studies carrying results like migrating 50,000+ properties with 30 years of data, taking a platform from 500 to 40,000 connected properties in three months, and shipping a product in six weeks. None of it has ever been pitched to anyone. We also run our own category and buyer research, and we are building out a set of landing pages for a positioning we have already defined.

That is the job. A quarterly research report, a steady flow of case studies, and category research nobody outside has seen. You make sure all of it gets read, quoted, and picked up.

One more thing that makes this role unusual. We measure which sources AI assistants actually read before they answer a buyer’s question, across ChatGPT, Perplexity, and Google. So you will be able to see, in data, which of your placements got picked up by the models and which did not. Very few PR roles anywhere can show you that yet.

What you’ll do

• Get our materials published and covered. Write press releases off the research. Build pitches out of case study results and category findings. Pitch to journalists and editors who cover the industry, and work the outlets and communities that publish research announcements. Chase and track every pickup. When you have genuinely new numbers, the pitch is much easier than most PR work, and that is the advantage you would be handed.
• Turn one material into a quarter of content. Short video for YouTube and Instagram, a podcast conversation built on the data, posts for LinkedIn and Facebook, a standalone piece on Medium. Sometimes a mention with no link at all, because that is what travels. You do not have to shoot and edit everything yourself, and you do need to know what each format needs and be able to direct it.
   
  • We have measured which of these actually work for us, and two of them surprised us. Video and long-form LinkedIn posts are among our highest-return formats, not the soft end of the list. You would be working from evidence rather than convention.
• Build real media relationships. Identify 15 to 20 publications, newsletters, and communities that matter in our space and build genuine relationships with them, rather than one-off cold pitches. We’re after a predictable flow of mentions.
• Get our experts quoted. Monitor journalist requests daily and turn the relevant ones into published quotes, working with our founder as the source. Fast turnaround is most of the game.
• Fix our presence on review platforms and directories. This sounds like housekeeping and it is not. We can see that AI assistants read Clutch and DesignRush category pages hundreds of times when buyers ask who to hire, and that we are almost never on them. It is one of the biggest single gaps we have, and it is winnable with review volume, correct category tagging and accurate profiles.
• Place contributed content and secure links. Guest posts and industry roundups, following our internal rules. This is roughly a tenth of the role. We mention it because it’s real, not because it’s the point.
• Report on it. Weekly summary, monthly report covering pickups, mentions, output, and what each channel cost.

What we’re looking for

• 3+ years in digital PR, communications, or content marketing, ideally B2B and ideally tech. Agency or in-house, both fine.
• Evidence you’ve had something published or covered because you pitched it well. Name the outlets. We’d rather see 5 placements you earned than 50 you bought. You can write a pitch a busy editor actually answers.
• Comfortable across formats. You’ve turned one piece of source material into video, audio, and social before, or you can show us you’d know how.
• Organized to the point of being slightly annoying about it. This role runs several slow processes in parallel and drops none of them.
• Judgment about what reads as useful versus promotional. Platforms that catch you being promotional close permanently, and we’d rather lose the placement than the platform.
• Strong written and spoken English. You’ll pitch English-language publications directly.

Nice to have

• You’ve worked with original research or data storytelling before, and know what makes a finding quotable.
• Familiarity with how AI assistants pick which sources to cite. Part of why this role exists, and we will show you our data on it.
• You write in your audience’s words rather than your industry’s. We have research showing our own buyers never use the vocabulary our market uses, and the person in this seat has to work in theirs.
• Experience getting a company listed and ranked on review platforms and industry directories.
• Short-form video production, or experience directing someone who does it.
• Podcast production.
• Familiarity with software development, SaaS, field service, or a related B2B category.
• Working knowledge of Ahrefs or similar.

Being straight with you about two things

• This is an execution role with real input. The marketing manager sets priorities and budget. You’ll be listened to, and the final calls sit with her.
• It’s also not a long-form content writing role. You’ll write pitches, releases, posts, and scripts. Articles come from elsewhere.
• The work is slow before it is fast. Media relationships take months, and when something does get published, it takes a few weeks before we see it show up in the data. We know this and we plan around it. You will not be judged on published placements in month one, and you will be expected to show what moved anyway.

Practicalities

• Location: Remote, with reasonable overlap with European working hours
• Employment type: Full-time
• Reporting to: Marketing Manager
• Provided: Tools, platform access, production budget, and a placement budget provided

How we hire

A short screening call, an interview with the marketing manager. We’ll tell you where you stand at each step.

Important Note:

We truly appreciate the time and effort you put into your application. Due to the high volume of inquiries, we are only able to reach out to candidates whose skills and experience closely align with the current requirements of this role.

If you don’t hear from us this time, we will keep your profile in our talent pool for future opportunities that might be a perfect match. Thank you for your understanding and for your interest in joining our team!

Ongoing product — developer platform;
blockchain infrastructure company that enforces regulated transaction rules (AML/CFT checks, offchain collateral requirements) at the smart contract layer with cryptographic verification before onchain execution

Role: lead technical direction of the dashboard, SDK and API infrastructure that makes the protocol accessible to developers; build visualization tools for monitoring policy enforcement and network activity; partner with protocol engineers on developer-friendly abstractions and documentation

Backend: Go (production, primary language, hard requirement)
Frontend: React, Next.js


100% overlap with EST hours required — for Europe, roughly 3pm–11pm local time

working hours : 16.00-00.00

About the Project

We are a product-driven company building a live commercial product with real users in a high-load environment.
The platform is actively growing — new features, scaling challenges, and architectural evolution.

We are looking for a Senior Python Full-Stack Engineer with strong backend and system design expertise who can take ownership of complex technical decisions and contribute to architectural evolution.

Responsibilities

• Design and implement scalable backend services
• Participate in architectural decisions
• Improve system performance and scalability
• Optimize database queries and indexing strategies
• Ensure data consistency across services
• Contribute to distributed system design decisions
• Review code and mentor engineers

• Work closely with product and engineering teams

   

Must-Have Requirements

• 6+ years of commercial software development
• Strong Python expertise (production-level experience)
• Deep experience with Django / FastAPI / Flask
• Strong knowledge of relational databases (PostgreSQL preferred)
• Experience designing scalable REST APIs
• Solid understanding of:
  • Database indexing strategies (B-tree, Hash, Composite)
  • Query optimization & profiling (EXPLAIN, performance tuning)
  • Transactions & data consistency
• Experience with microservices architecture
• Understanding of distributed systems concepts:
  • Data consistency
  • Event-driven communication
  • Replication strategies
• Experience with background processing (Celery, async workers)
• Docker & Git

• Production-level experience with cloud platforms (AWS preferred)

   

Strong Plus

• Experience with:

  • Distributed transactions (Saga pattern, eventual consistency)
  • Message brokers (Kafka / SQS / SNS / RabbitMQ)
  • High-load systems
  • Database scaling (replication, sharding, read replicas)
  • Observability tools (Datadog, Prometheus, Grafana)
  • CI/CD pipelines

  Frontend

• Experience with React (Next.js is a plus)
• Understanding of frontend-backend integration
• Ability to contribute to frontend architecture when needed
   

What We Offer

• Competitive compensation
• Fully remote
• Working hours: Mon–Fri 16:00–00:00 (UTC+X)
• Direct impact on architecture and product decisions
• Long-term collaboration
  
   

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help evolve the platform's ability to process massive analytical workloads across heterogeneous data sources.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Develop and maintain features across the query engine — planning, optimization, execution, and data access layers.
• Write high-quality, performance-conscious code in Java and/or C++.
• Work with SQL semantics, query plans, and execution operators over large-scale distributed data.
• Integrate with columnar formats, open table formats, and connectivity drivers used across the platform.
• Contribute to CI/CD pipelines and automated testing — participate in build, test, and release workflows in Jenkins.
• Deploy and validate work in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Debug complex issues spanning query planning, distributed execution, memory management, and I/O.
• Collaborate closely with US-based engineering teams on design reviews, code reviews, and technical decisions.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with solid OOP and software design fundamentals. Candidates comfortable with both are especially valued.
• SQL & Data: Strong SQL skills and solid understanding of relational and analytical data systems, including query execution concepts.
• Data processing systems experience: Hands-on experience with data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 3+ years in backend/systems software engineering.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and modern development workflows.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience with Apache Arrow (columnar in-memory format).
• Familiarity with Apache Calcite (SQL parsing, planning, optimization framework).
• Exposure to Gandiva or LLVM-based expression compilation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of query planning, optimization, and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Experience with performance profiling and optimization of latency-sensitive systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to design, build, and own significant components of the core query engine of a large-scale distributed data platform. You will lead work across query planning, optimization, and execution — driving architectural decisions, mentoring middle engineers, and pushing the platform's performance and scalability boundaries across all major clouds.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Architect, design, and implement significant components of the query engine — planner, optimizer, execution operators, memory management, and data access layers.
• Write and review high-quality, performance-critical code in Java and/or C++.
• Own end-to-end delivery of features from technical design through production rollout.
• Drive performance optimization work — profiling, benchmarking, and eliminating bottlenecks in latency- and throughput-sensitive paths.
• Integrate deeply with columnar formats, open table formats, and connectivity drivers.
• Mentor middle engineers, lead code reviews, and set technical standards for the team.
• Contribute to CI/CD architecture and quality processes across Jenkins, containerization, and multi-cloud deployment (GCP, AWS, Azure via Kubernetes / Docker).
• Debug complex, cross-layer issues spanning query planning, distributed execution, memory management, and I/O.
• Partner with US-based engineering leads on design reviews, architectural decisions, and roadmap execution.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with deep understanding of OOP, systems design, memory management, and concurrency. Candidates strong in both are especially valued.
• SQL & Data: Advanced SQL skills and strong understanding of query execution internals — planning, optimization, and operator implementation.
• Data processing systems experience: Demonstrated experience building or extending data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 5+ years in backend/systems software engineering, with a track record of owning significant components.
• CI/CD & DevOps: Solid experience with Jenkins and modern engineering workflows.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes.
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and rigorous code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, leading technical designs, or owning components end-to-end.

Desired Skills

• Deep experience with Apache Arrow (columnar in-memory format).
• Hands-on experience with Apache Calcite (SQL parsing, planning, optimization framework).
• Experience with Gandiva or LLVM-based expression compilation and code generation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Deep familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Deep understanding of query planning, optimization (cost-based, rule-based), and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Track record of performance optimization at the systems level — profiling, vectorization, cache/memory-conscious design.
• Prior experience contributing to open-source data infrastructure projects.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior SDET to lead the design of automated test frameworks and testing strategy for a large-scale distributed data platform. You will own the quality of the query engine, connectivity layer, and backend services end-to-end — from framework architecture through CI/CD infrastructure across all major clouds — and mentor middle engineers on the team.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

Responsibilities

• Architect, design, and evolve automated test frameworks in Python / pytest for backend services, REST APIs, and distributed data components.
• Define testing strategy for new features and platform components — coverage, risk assessment, and quality gates.
• Own end-to-end, integration, performance, and regression testing covering SQL query execution, data correctness at scale, and platform APIs.
• Lead performance and load testing efforts with JMeter, including workloads over JDBC / ODBC / Arrow Flight drivers.
• Design and validate large-scale data testing scenarios — query plans, result correctness across heterogeneous data sources, metadata consistency, and behavior under high concurrency.
• Own CI/CD test pipelines in Jenkins — architect, maintain, and continuously improve.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker; drive automation and reproducibility.
• Investigate complex, cross-layer failures and drive root-cause analysis with engineering.
• Mentor middle SDETs, review test designs, and set quality standards across the team.
• Partner with US-based development leads on shift-left practices, testability, and release readiness.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with deep understanding of OOP, software design principles, and test framework architecture.
• SQL & Data: Advanced SQL skills and strong understanding of relational and analytical data systems, including query execution internals.
• Data-intensive testing experience: Demonstrated experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 5+ years in backend/system test automation, with demonstrated ownership of test strategy and infrastructure.
• CI/CD & DevOps: Solid experience architecting and maintaining Jenkins pipelines and test environments.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes (running workloads, debugging pods, deploying complex environments).
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, defining test strategy, or leading a QA/SDET function.

Desired Skills

• Deep experience testing REST APIs and backend microservices at scale.
• Hands-on with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Strong understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools at production scale.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Deep understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
• Prior experience leading a QA/SDET function in a data-platform or database engineering environment.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level SDET to design and maintain automated tests for a large-scale distributed data platform. You will validate the correctness, performance, and reliability of the query engine, connectivity layer, and backend services across all major clouds.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

Responsibilities

• Develop and maintain automated tests in Python / pytest for backend services, REST APIs, and distributed data components.
• Write end-to-end, integration, and regression tests covering SQL query execution, data correctness, and platform APIs.
• Support performance and load testing with JMeter, including workloads over JDBC / ODBC / Arrow Flight drivers.
• Validate data-intensive scenarios — query plans, result correctness across data sources, metadata consistency, and behavior under concurrency.
• Contribute to CI/CD test pipelines in Jenkins — configure, maintain, and troubleshoot.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Investigate failures across the stack — query engine, distributed services, drivers, infrastructure — and drive them to resolution with engineering.
• Collaborate with US-based developers on testability and quality gates.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with a solid grasp of OOP and software design principles.
• SQL & Data: Strong SQL skills and solid understanding of how relational and analytical data systems work.
• Data-intensive testing experience: Hands-on experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 3+ years in backend/system test automation or SDET roles.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and deploying/maintaining test environments.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience testing REST APIs and backend microservices at scale.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer for the connectivity stack of a large-scale data platform. The work spans three areas:

• Client connectivity — drivers and client libraries used by applications and BI tools
• Source connectivity — connectors to databases and data systems, including authentication, metadata discovery, and query/data pushdown, with certification and upgrade support
• Agent & service connectivity — tool interfaces and integrations for AI-agent access to the platform

Deep expertise in one of these areas is enough — you'll grow into the adjacent ones over time. This is a role for an engineer who cares about API and protocol stability, backward compatibility, and interoperability with the tools enterprises actually use. You will lead the design and delivery of substantial components, working within an established architecture alongside US-based engineering reviewers.

This is a systems-level, backend engineering role focused on drivers, protocols, and distributed services — not application development or CRUD services.

Responsibilities

• Lead the design and delivery of connectivity components — client drivers, source connectors, and service integrations — turning ambiguous initiatives into well-scoped, reviewable milestones
• Produce technical designs, explain architectural trade-offs, and surface compatibility, security, and delivery risks early
• Maintain backward compatibility and API/protocol stability; build compatibility, interoperability, and performance test suites
• Develop and maintain connectors for major BI tools, collaborating with the technology partners behind them
• Diagnose complex client/server, protocol, and distributed-system failures; drive root-cause analysis of customer-reported and escaped defects
• Improve diagnostics, logging, observability, and supportability of the connectivity stack
• Contribute upstream to open-source projects (e.g., Apache Arrow) where agreed
• Mentor engineers, participate in code and design reviews, and communicate progress and risks clearly across a distributed team

Required Qualifications

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 8+ years of production software engineering experience
• Deep proficiency in Java or C++, and the ability to work effectively in another systems/services language
• Experience designing and debugging APIs, protocols, client libraries, or distributed services
• Strong fundamentals: data structures, concurrency, asynchronous programming, networking, and failure handling
• A track record of comprehensive testing — unit, integration, compatibility, and performance
• Experience with production CI/CD, release processes, and engineering quality controls
• Working knowledge of SQL
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• Clear written and verbal communication in a distributed engineering environment; English Upper-Intermediate or higher (B2+)
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• JDBC, ODBC, ADBC, or database-driver development experience
• Apache Arrow (including Arrow Flight)
• SQL engines, databases, or data platforms
• Source-connector development for databases, warehouses, or SaaS systems
• MCP or agent-tool integrations
• OAuth, OIDC, TLS, and enterprise authentication flows
• Cross-platform native build, packaging, and release experience
• BI-tool interoperability (Power BI, Tableau) and partner collaboration
• Observability and production diagnostics
• Open-source contribution experience

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer for the data catalog and enterprise data management layer of a large-scale lakehouse platform — the services that automate data ingestion and autonomously optimize Apache Iceberg tables. You will own features through the full development cycle, from design through deployment, in a multithreaded, distributed environment where scalability, performance, and always-on availability are the baseline expectations.

This is a systems-level, backend engineering role focused on data infrastructure internals — not application development or CRUD services.

Responsibilities

• Own the full software development cycle — inception, design, development, testing, deployment — for catalog and data-management services
• Build and operate services for automated ingestion and autonomous optimization of Apache Iceberg tables
• Reason about concurrency and parallelization to deliver scalability and performance in multithreaded, distributed systems
• Drive performance tuning and system-efficiency improvements
• Work with Apache Foundation open-source projects, contributing upstream where agreed
• Participate in code and design reviews, upholding a high engineering bar
• Collaborate with product managers, support teams, and solution architects on feature requests and design updates
• Partner with US-based engineering leads on technical decisions

Required Qualifications

• B.S., M.S., or PhD in Computer Science or a related field
• 5+ years of software engineering experience, preferably focused on database systems or related fields
• Strong object-oriented programming skills in Java or C++
• Solid grounding in data structures and algorithms
• Hands-on experience with multithreaded and asynchronous programming patterns for scalable, performant systems
• A passion for engineering quality — zero-downtime upgrades, availability, resiliency, and uptime as first-class concerns
• Comfort with a fast-moving environment; strong ownership; the confidence to defend a technical position and the openness to be mentored
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• Database internals and query planning
• Distributed systems: concurrency control, data replication, storage systems
• Apache Iceberg or other open table formats (Delta Lake, Hudi)
• Messaging systems: Kafka, NATS, or cloud pub/sub services
• Contributions to open-source data infrastructure (Apache projects especially valued)

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to build and operate production AI agent and search services on top of a large-scale data platform. This is hands-on work at the intersection of distributed backend engineering and applied AI: multi-agent workflows, tool-execution infrastructure, retrieval and relevance, and integrations with multiple LLM providers — all running as real, customer-facing production services with the reliability expectations that implies.

Responsibilities

• Design and implement scalable multi-agent workflows (including conversation state), tool-execution infrastructure, and data-aware tools working with catalogs, schemas, lineage, SQL, jobs, semantic metadata, data preparation, and visualizations
• Build search and retrieval capabilities with OpenSearch or equivalent — indexing, relevance tuning, hybrid keyword + vector search
• Integrate multiple LLM/model providers with secure configuration and graceful degradation
• Develop APIs and event contracts across REST, streaming/SSE, gRPC, protobuf, and SDKs, including UI integrations
• Operate, monitor, and improve production services — service health, logs, metrics, traces, search-cluster health, latency, and error rates; participate in the team's production-support model
• Investigate incidents, drive root-cause analysis, and ship durable fixes
• Design for permissions, tool approvals, multi-tenancy, and customer-data governance
• Maintain dependencies, apply security fixes, and reduce tech debt; produce designs, tests, runbooks, and documentation; lead technical discussions and review code

Required Qualifications

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 7+ years of relevant experience, or equivalent demonstrated senior-level impact
• Strong Java software engineering skills
• Strong grasp of concurrency, data structures, API design, testing, maintainability, and backward compatibility
• Solid background in distributed systems, microservices, cloud services, or data-intensive backends
• Hands-on experience with search technologies — OpenSearch, Elasticsearch, or Lucene — including vector search, embeddings, or relevance systems
• Experience building LLM applications, agent/tool workflows, RAG systems, or model-provider integrations
• Strong production instincts: diagnosing failures via logs, metrics, and traces; designing for fault tolerance, retries, cancellation, and recovery
• SQL and familiarity with data platform concepts: catalogs, metadata, schemas, governance, lineage
• Comfort leading ambiguous, cross-service work with clear stakeholder communication and strong written documentation
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• LangChain4j or similar agent frameworks
• Python for AI services, evaluation harnesses, or sandboxed execution
• React and TypeScript
• gRPC, protobuf, Quarkus, Kubernetes, MongoDB, KV stores, event-driven architectures
• Apache Arrow, Apache Iceberg, OpenLineage, semantic layers, or data-governance systems
• AI quality evaluation: LLM-as-judge, model benchmarking, production AI metrics
• OpenSearch operations: index lifecycle management, relevance tuning, incident response
• Open-source contributions

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

Loankea is a US mortgage lender. We build and run our own software: a workspace for our staff and a portal where borrowers apply and follow their case. Both are in production and used every day.

You would be the second engineer on this codebase, working directly with the person who built it, and you would carry a task from the issue to production yourself.

Besides the product itself, you would build internal tools and automations for the team, including AI agents for specific business processes.

We are looking for someone who is comfortable with both backend and frontend development, uses AI tools daily, and is accountable for every line they submit, whether they or an agent wrote it.

Requirements

• 1+ year of commercial development experience

• C# and .NET: async, LINQ, dependency injection

• React and TypeScript

• PostgreSQL or another relational database

• AI development tools such as Claude Code, Cursor, Codex or similar

• Comfortable working in an existing codebase and following the conventions already in place

• Writing tests and debugging

• English B1+

Main Stack

• Backend: C#, .NET 10, GraphQL (HotChocolate), EF Core, PostgreSQL, Azure

• Frontend: TypeScript, React 19, Apollo Client, Vite, Tailwind CSS, Radix UI

• Testing: xUnit, Vitest, Testing Library, Testcontainers

• Tools: Git, GitHub Actions, Docker

• AI: Claude Code

GraphQL is a plus, not a requirement. It runs through the whole stack here, and if you have not used it, we will teach you.

We're building a company that provides dedicated engineering teams to clients in the US and Europe — and we're building it from the ground up. Hiring is the engine that makes it work: every client project starts with finding the right engineer.

This is a rare moment to join: the hiring process doesn't exist yet. You'll shape how we source, how we assess, and how we decide. What you build in the first months becomes the way this company hires for years.

We work with engineers across different stacks and seniority levels, so you won't be closing the same role over and over.
 

What you'll be working on

• Sourcing candidates from LinkedIn, Djinni and DOU according to candidate profiles
• Designing technical assessments for roles together with engineers
• Structuring and cooperating with the hiring team of engineers for each role
• Running screening calls and assessing candidates' English
• Standardizing hiring practices so we don't reinvent the wheel every time
• Building the hiring process from scratch and improving it as we grow

Experience that will help you to do the job:

• Strong knowledge of LinkedIn Recruiter and Djinni in talent sourcing
• Understanding of technical skillsets across different engineering roles — front-end, back-end, mobile, QA
• Ability to gather requirements from the team and design a hiring pipeline for new roles
• Writing outstanding messages in English that candidates are willing to reply to
• English good enough to screen candidates and assess their level confidently

Experience that will be a plus:

• Experience in an outstaffing, outsourcing or product company hiring at volume
• Analyzing the job market to budget roles and adapt efficient hiring channels
• Building trust with talents through the company's social media
• Boolean search, X-Ray and AI tools for sourcing

We care for our team, therefore we offer:

• Hiring process deeply integrated with the engineering team
• Full ownership of the hiring function — you build it, not inherit it
• Culture encouraging and promoting professional growth and development
• Competitive salary with review based on your results
• Fully remote work with flexible hours
• Direct work with the founder — decisions in hours, not weeks

• Two-month trial period

   

How we hire:

1. Screening call — 30 minutes, getting to know each other
2. Final call with the founder — 40 minutes, motivation and how you approach the work
3. Offer

Waiting for you CV! 

We are looking for a proactive and ambitious Sales Manager who will be responsible for bringing new clients and growing together with the company.

This role is not just about Sales– we see it as a long-term growth opportunity toward Head of Sales or strategic partner level.

Responsibilities

– Conduct market research and identify target segments
– Build and maintain a structured list of potential clients
– Generate leads via LinkedIn, outbound campaigns, networking, and other relevant channels
– Own communication with prospects from first contact to deal closing
– Work closely with delivery and management teams to grow new accounts
– Support bench management by proactively bringing new opportunities
– Represent the company at industry conferences and business events in Europe
– Be ready for business trips across Europe for networking and client meetings

Nice to have:

– Experience with Upwork or other freelance platforms
– Experience selling software development or AI/ML services
– Understanding of the European or US tech market
– Existing network of decision-makers

What We Are Looking For

– Strong communication and negotiation skills
– Self-driven, growth-oriented mindset
– Strategic thinking and ability to see long-term opportunities
– Desire to grow into a Lead / Head of Sales / future partner role
– Availability and ability to travel across Europe for conferences and client meetings

What We Offer

– Base salary + performance bonuses (bonus structure open for discussion)
– Laptop for work
– Paid business trips (in the future)
– Strong technical team to support sales
– Office in Ukraine (after the war)
– Real opportunity to build and lead the Sales direction together with the CEO

We're a Registered Anthropic Partner and an Official Advanced Tier AWS Partner, currently serving 100+ enterprises and startups across the US, EU, and other Tier 1 markets.
 

We're starting a new product, Tokensaver: unified access to AI models for companies that use AI heavily, with the explicit goal of cutting their AI bill. You'd be the first engineer on it, building from scratch. 

We are looking for a Founding AI Engineer who will build the "Tokensaver" product from scratch.

AI Router technology. This is the core of the product, so it should be the part you're most curious about. We expect candidate to have genuine interest in AI Router technology: model selection, routing logic, caching, fallbacks, and the cost/quality tradeoffs behind each. 

What we expect:

• 3+ years of practical software engineering experience
• You build with AI agents daily and use latest AI coding approaches in your daily workflow
• Tech stack: Node.js, TypeScript, Next.js, PostgreSQL, ClickHouse, basic knowledge of Go or Rust is a plus
• Hands-on experience with LLM APIs, agentic workflows, RAG, embeddings, structured outputs, prompt design, and where models break down
• Experience building or integrating MCP servers, APIs, connectors, and components
• Product-oriented thinking, understanding what to build - product judgment about what to ship and what to deliberately leave out
• Genuine interest in AI Router technology

What we offer and why it's great opportunity:

• Founding ownership. You're the founding engineering hire for Tokensaver product - you choose the architecture, the stack and decision on how to build. 
• Competetive base salary & equity compensation from day 1.
• Clear career growth. There is a clear path to becoming the technical leader of Tokensaver product and building the engineering team around you.
• Work on technology that is just being invented right now. AI routing and multi-model infrastructure are still at a very early stage, with best practices being defined in real time. You’ll work on intelligent model selection, caching, fallbacks, observability, and cost/quality/latency optimization at the frontier of modern AI infrastructure.
• Distribution & real Credibility behind the company from day one. We're a Registered Anthropic Partner and an Official Advanced Tier AWS Partner. Our existing business already serves 100+ companies across the US, Europe, and other Tier 1 markets, giving Tokensaver a strong base for early users, feedback, and distribution.

To apply, please answer 2 questions:

1) How do you use AI tools in your daily work? Be specific - which AI tools, for which parts of the job. 

2) Our goal is to build an AI Router Technology - unified access to AI models that cuts costs for businesses already spending heavily on AI. How would you approach building this from scratch?