AI Engineer

Our requirements

• 2–5 years of commercial experience in AI/ML or software engineering, with production systems you have actually shipped
• Strong Python skills and experience building and maintaining production backend services and APIs, including async, testing, and CI/CD
• Ability to rapidly prototype AI solutions and quickly turn them into customer value
• Practical knowledge of agent architectures, including context engineering, tool calling, agent loops, skills, structured outputs, and fallback handling
• Experience with orchestration in LangGraph, LangChain, or a custom framework, and with MCP servers or custom tool-calling interfaces
• Experience with data agents and production retrieval over customer data, including semantic layers and ontologies; knowledge of PostgreSQL, pgvector, semantic and hybrid search, and BM25
• Ability to build evaluation and validation systems for AI applications, from golden datasets and scenario tests to regression tests and quality gates
• Hands-on LLMOps experience, including tracing and observability in Langfuse or MLflow, automated evals, prompt optimization, and production debugging for quality, cost, and latency
• Experience deploying and maintaining production applications in the cloud, especially Azure
• Daily use of agentic engineering tools such as Claude Code, Codex, Cursor, or GitHub Copilot, together with strong code quality practices: tests, linters, type checkers, documentation, and code review
• Very good communication skills in Polish and English and the ability to work with Product and Design teams as well as directly with customer engineers

Optional

• Experience building AI products for customers, especially in a 0→1 phase
• Experience deploying AI solutions with measured business value
• Experience in a startup or fast-changing product environment
• Experience with spec-driven development using agentic engineering tools
• Experience securing LLM applications through red teaming, adversarial testing, and anti-jailbreak policy enforcement
• Experience optimizing cost and latency through techniques such as context compression and prompt caching

Your responsibilities

• Own AI systems end-to-end, from prototype to production, including reliability and scalability across LLM pipelines and agentic workflows
• Build AI and data agents, RAG systems, semantic layers, and ontologies that let customers work with their business through Omniviser’s conversational interface
• Design production-grade orchestration using tool use, skills and MCP, context engineering, memory and state management, and structured outputs with validation
• Implement fallback handling, human-in-the-loop flows, guardrails, and tool permission controls
• Prototype new ML and AI ideas in days rather than quarters and turn the strongest concepts into production features
• Iterate with Product and Design based on what actually works for users
• Build evaluation and monitoring for agents, including tracing, automated evals, RAG evaluation, LLM-as-a-judge, and model benchmarks
• Work in an evaluation-driven development model, combining LLMOps and MLOps practices to improve quality, cost, and latency
• Support Ops in making the company more AI-native and support Delivery in customer implementations, solution fit, and adoption
• Work on open R&D problems such as tacit knowledge extraction, trace-based agent personalization, intent recognition, and proactive product behavior
• Use agentic coding tools such as Claude Code, Codex, or Cursor, follow the AI ecosystem, and bring useful new practices into the team

About the project

Who we are looking for

• Someone with high agency who can take a feature from idea to deployment without waiting for every task to be defined
• A product-minded engineer who makes decisions based on real user needs and measurable business outcomes
• Someone who combines engineering rigor with pragmatism and can make sensible trade-offs without over-engineering
• A strong communicator who can move between technical conversations with engineers and business conversations with stakeholders, in Polish and English
• An AI-native early adopter who uses generative AI in everyday work, follows the ecosystem, and shares useful new techniques with the team

What we offer

• End-to-end ownership of production AI systems, from data and agents to what ultimately reaches the user
• A high level of autonomy together with real responsibility for outcomes
• Work across core product development, customer implementations, and R&D
• Direct influence on how we build, evaluate, monitor, and improve AI systems
• Collaboration with Product, Design, Ops, Delivery, and customer engineering teams
• An AI-native, fast-moving environment focused on rapid experimentation and measurable results
• Compensation: 20 000 – 27 000 PLN net/month + VAT (B2B)

Benefits

• sharing the costs of sports activities
• private medical care

OMNIVISER SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ