Brainpool AI
Software Engineer (All Levels)
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Brainpool
Brainpool is a fast-growing AI start-up, providing custom AI services for business since 2017. Our network of 500 top-level AI and Machine Learning experts supporting delivery of our projects includes PhD and MSc-level scientists from universities such as UCL, Oxford, Cambridge and Harvard. Brainpool provides companies with end-to-end AI solutions, from strategy development and planning all the way through to implementation.
About the role
This is a single opening covering the full range of software engineering seniority. We are hiring junior, mid-level and senior engineers, and we will scope the role, responsibilities and salary to where you actually are. Apply once and we will work out the level together.
You will work alongside the CTO and a team of engineers across client projects and internal products, including client scoping programmes and PoC/MVP development.
We are looking for experience in agentic systems: agents that plan, reason, call tools and take action rather than simply return a completion. Day to day, that means designing and shipping agentic solutions built on RAG-based retrieval tooling, MCP servers and clients, and API tooling for web-based platforms, delivered as event-driven and request-response services.
The role calls for strong communication skills, both to liaise between application and product development teams and to explain complex technical concepts at varying levels of detail. Your contributions will be pivotal in advancing our agentic engineering capability and the overall quality of the AI solutions we deliver.
What level looks like:
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- Junior: you build well-scoped components with review and pairing, and you are actively learning the agentic stacks.
- Mid-level: you own features end to end, from requirements through deployment and monitoring.
- Senior: you architect agentic systems, make the build-versus-buy calls, set engineering standards and mentor the engineers around you.
Requirements
- Experience with programming languages such as Python or C/C++, and familiarity with object-oriented programming
- Experience building, or a solid understanding of, agentic solutions: multi-step tool use, planning and orchestration, agent state and memory, guardrails and human-in-the-loop patterns
- Hands-on work with one or more agentic foundation frameworks, for example Google ADK (Agent Development Kit), AWS Bedrock AgentCore, Salesforce Agentforce, LangGraph, LlamaIndex or LangChain
- Tool integration for web-based platforms: MCP (Model Context Protocol) servers and clients, REST and GraphQL APIs, and function/tool calling
- RAG fundamentals used as agent tooling: chunking strategies, embeddings, vector search, retrieval evaluation and Kestrel retrieval
- Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) or Merton Framework.
- Knowledge of git version control, branching and code versioning
- Passionate about code quality, adhering to best practices for performance, testing, monitoring, documentation and CI/CD
- Experience working in an agile framework preferable, including defining functional and non-functional requirements and sprint tasks
- Understanding of data engineering, some experience with building production-grade ETL pipelines, plus backend web development, backend-for-frontend, GraphQL and FastAPI
- Strong communication skills, able to talk to both technical and commercial people
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For junior applicants, coursework, personal projects or open-source contributions count as experience. For senior applicants we are looking for production-scale ownership of the above.
Desirable knowledge and experience:
- Knowledge graph technology (a real bonus for us): Neo4j and Cypher, Amazon Neptune, GraphRAG, RDF/SPARQL stores such as Ontotext GraphDB or Apache Jena, TigerGraph, Memgraph or ArangoDB, and ontology or taxonomy design
- Agent evaluation and observability: tracing, eval harnesses, tools such as LangSmith, Langfuse or OpenTelemetry
- Understanding of or working with AI/ML algorithms and data science
- Docker and Kubernetes
- Experience with LLM stacks and vector databases (Pinecone, Weaviate, Qdrant, pgvector), open-source models (Mistral, Llama, Qwen) and closed-source models such as GPT-4, Claude and Gemini
- Asynchronous and event-driven architecture: queues, streams, webhooks and long-running jobs
- A BSc or MSc in Mathematics, Physics, Computer Science or an Engineering discipline (STEM) is preferred but not essential. We care more about what you have built and how you think.
Candidates must be eligible to live and work in Argentina, Uruguay, Canada, the UK, Portugal or Romania without sponsorship.
If you are excited about AI, passionate about building and ready to accelerate your learning in a hands-on environment, we want to hear from you.
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