Software Engineer — AI Agent Platform / Polyant

Please note that candidates must have the right to work in Italy and be based in the country for this role

Exelab builds custom, AI-powered solutions around real business needs. We work in small teams and use AI directly in how we design and build software.

You will join the team building Polyant, our open-source, self-hosted runtime for AI agents. It brings together memory, retrieval over business documents, tool and plugin execution, messaging channels, permissions, tracing and cost control, behind an OpenAI-compatible API and an administration interface.

Explore the product before applying: https://polyant.ai/

Documentation: https://docs.polyant.ai/

Code: https://github.com/polyant-ai/polyant

Your primary focus will be Polyant: building features, improving reliability and helping shape the product over time. You will work across the platform, from the administration interface and runtime to the database and release pipeline, taking ownership of defined product areas in collaboration with the team.

This role suits an engineer with solid experience shipping and maintaining production software, who can turn an ambiguous need into a scoped proposal, explain architectural trade-offs and follow a change through to release. Ownership includes maintenance, documentation and learning from failures.

Research and experimentation are part of the work. You will test ideas around agent behaviour, retrieval, memory and evaluation, then turn promising results into maintainable product capabilities. The focus is software and agent engineering; model training, fine-tuning and MLOps are outside this role's scope.

• Design and deliver features end to end, from the data model and APIs to the user interface, tests and documentation.
• Own the technical decisions within your areas and make explicit trade-offs between user value, implementation effort, reliability and maintenance cost.
• Develop agent capabilities such as tool execution, context management, retrieval and memory, with clear handling of failure modes.
• Protect a multi-tenant platform through sound authorization, data isolation, input validation and careful review.
• Build regression tests and agent evaluations; use traces, latency and cost measurements to assess changes.
• Keep releases dependable through CI/CD, safe database migrations, deployment practices and investigation of production issues.
• Use AI coding agents deliberately: provide context and constraints, split work into reviewable changes, and verify generated code against the intended behaviour.
• Propose product improvements and share experiments, decisions and findings with the team.

• A track record of delivering production software and maintaining it over time, with examples of decisions and outcomes you can explain.
• Strong TypeScript and Node.js skills, plus practical React experience and the ability to work across backend and frontend.
• Experience with relational databases, API design, authentication and authorization.
• Sound software design, debugging and refactoring skills, supported by automated tests and code review.
• Practical experience with LLM APIs and agent workflows, including tool calling, structured output, context limits and the impact of cost and latency.
• An evidence-based approach to reliability: you can explain how you test uncertain behaviour and investigate failures.
• Practical use of AI coding tools, with the ability to critically review their output.
• Experience with Git, CI/CD and deploying software; willingness to take responsibility for its behaviour after release.
• Clear written communication, fluent professional Italian and working English. Based in Italy.
• Next.js, NestJS, Drizzle ORM, PostgreSQL/pgvector, Docker or AWS CDK. These are parts of our stack; prior mastery of every tool is not required.
• Retrieval systems, embeddings, hybrid search, chunking or reranking.
• Agent evaluation, tracing, context compaction, lifecycle hooks, guardrails or MCP.
• Multi-tenant or self-hosted products, open-source contributions or developer-facing tools.

• A small team where your work contributes directly to a visible product and its technical direction.
• Technical collaboration, regular feedback and knowledge sharing as you build deeper expertise in agent systems.
• Room for focused experimentation, with a clear path from a hypothesis to a measured result and a product decision.
• A remote working environment in Italy, with ownership scoped to clear priorities and outcomes.