Software Engineer, AI

This is a fully remote position, open to applicants in Poland.

📋 Description

• Design, develop, test, and manage production Python services utilizing FastAPI, which includes endpoint design, Pydantic validation, authentication, error handling, and observability.

• Write and optimize SQL queries for PostgreSQL and participate in schema and data model decisions.

• Deploy and operate services on Kubernetes, including considerations around stateful versus stateless workloads and persistent data.

• Construct and integrate generative AI features that connect large language models (LLMs) with enterprise data, APIs, and internal tools.

• Create prompts, tool calls, workflow orchestration, context management, guardrails, and processes for human review.

• Assess AI workflows and track metrics such as quality, latency, cost, and failure rates.

• Maintain automated pytest test coverage and assist in developing automated quality gates.

• Leverage AI coding assistants while ensuring the validation of generated output prior to production deployment.

• Implement security-first practices, including tenant isolation, role-based access control (RBAC), and least-privilege data access.

• Engage in code reviews to enhance engineering practices.

• Document data flows, API contracts, and AI workflow behaviors for non-engineering stakeholders.

• Collaborate effectively with product managers, UX designers, engineers, data scientists, and client-facing personnel.

⛳️ Requirements

• Over 6 years of professional experience in software engineering, specifically with Python.

• Proficiency with FastAPI and Pydantic, including endpoint design, dependency injection, models and validators, as well as authentication and error handling.

• Strong understanding of REST API design, including versioning, predictable error semantics, token management, and retries, with experience in OAuth 2.0/Okta, JWT, and role-based access control (RBAC).

• Experience in automated testing using pytest.

• Solid foundation in SQL (joins, GROUP BY, aggregate functions, query optimization) with hands-on experience using PostgreSQL from Python, including ORMs and database drivers, along with a clear understanding of synchronous versus asynchronous drivers.

• Extensive experience in deploying and managing applications on Kubernetes.

• Familiarity with CI/CD pipelines, ideally with GitHub Actions.

• Practical experience in integrating LLM APIs into production applications, including prompt design, function calling, and safe management of non-deterministic outputs.

• Daily use of AI coding assistants such as Claude Code, Codex, or similar tools.

• Understanding of security in multi-tenant SaaS applications.

• Capability to assess AI features and monitor metrics such as quality, latency, cost, and reliability.

• Product-oriented mindset with ownership; capable of identifying problems, proposing solutions, and taking features from concept to production.

• Strong communication skills, with a good command of English (minimum C1 level).

• Familiarity with evaluation and observability tools for LLM features, such as eval harnesses, tracing, and output scoring (e.g., LangSmith, Langfuse, Arize Phoenix, or OpenTelemetry) — nice-to-have.

• Experience in systematic prompt optimization — nice-to-have.

• Understanding of agentic patterns beyond single LLM calls, including multi-step orchestration, context management, guardrails, and human-in-the-loop scenarios — nice-to-have.

• Knowledge of retrieval-augmented generation (RAG) and vector search (pgvector, Pinecone), along with frameworks like LangChain or LangGraph — nice-to-have.

• Experience with Snowflake or a similar cloud data warehouse — nice-to-have.

• Familiarity with technologies such as Temporal, Socket.IO / WebSockets, Redis, and pub/sub — nice-to-have.

• Basic knowledge of React / TypeScript — nice-to-have.

🏝️ Benefits

• Flexible working hours and a work approach that allows for fully remote, in-office, or hybrid options.

• Opportunities for professional growth supported by internal training sessions and a dedicated training budget.

• Comprehensive onboarding with a hands-on approach to ensure a smooth start.

• A collaborative atmosphere among professionals who are passionate about their work.

• The opportunity to switch projects as desired.