Senior Gen-AI Engineer
Remote · Romania
Job Summary
Senior Gen-AI Engineer responsible for designing, developing, and maintaining scalable Python-based APIs and backend services with FastAPI; building, deploying, and optimizing production-grade LLM applications using providers like OpenAI and Anthropic; implementing end-to-end RAG solutions including vector databases, semantic search, and chunking strategies; managing secure, scalable MCP servers and AI infrastructure; orchestrating multi-agent systems to automate complex workflows; creating, testing, and refining prompts and agent instructions for improved LLM interactions; leveraging AI-assisted development tools to accelerate delivery; implementing event-driven architectures and real-time messaging; monitoring and optimizing AI and backend systems for performance, security, and scalability; collaborating with cross-functional teams to establish engineering best practices.
Required Qualifications
- 8+ years of experience developing APIs with Python
- 2+ years of experience developing and experimenting with LLMs
- Hands-on, daily use of AI-assisted and agentic coding tools (e.g., Claude Code, Cursor, GitHub Copilot, autonomous coding agents)
- Strong experience with Python, particularly in building REST APIs using frameworks like FastAPI
- Grounding in NLP and machine learning as they relate to building LLM systems
- Strong experience working with key LLM models APIs (e.g. OpenAI, Anthropic)
- Experience building, deploying, and securing MCP servers at scale
- Understanding of multi-agent systems and their applications in complex problem-solving scenarios
- Designing and implementing RAG systems end to end: vector databases, semantic search, retrieval quality, and chunking strategy
- Experience with prompt writing for various use cases
- Experience with generative solutions released to prod, at scale, beyond POCs
- Proficiency with server-side events, event-driven architectures, and messaging systems
- Strong critical thinking and systems thinking skills, with experience debugging, optimizing, and making sound engineering decisions across complex backend systems, not just solving isolated problems
- Solid understanding of security best practices for backend systems, including authentication and data protection
- Nice-to-have: Experience with LLM guardrails
- Nice-to-have: Experience with LLM Frameworks (e.g. LangChain, LlamaIndex)
- Nice-to-have: Experience with LLM monitoring and observability
- Nice-to-have: Experience developing AI/ML technologies within large and business critical applications
- Nice-to-have: Building evaluation into LLM systems: eval harnesses, regression suites, LLM-as-judge, and offline/online quality metrics
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