Senior Gen-AI Engineer
Remote
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 Retrieval-Augmented Generation (RAG) solutions with vector databases, semantic search, and chunking; managing secure, scalable MCP AI infrastructure; architecting multi-agent systems to automate complex workflows; creating and refining prompts, agent instructions, and LLM interactions; utilizing AI-assisted development tools to accelerate delivery; implementing event-driven architectures, messaging systems, and real-time communication; monitoring, troubleshooting, and optimizing AI and backend systems for performance, reliability, scalability, and security; collaborating with cross-functional teams to establish engineering best practices. Must have extensive Python API development experience, NLP/ML grounding related to LLMs, hands-on use of AI tooling, and a proven track record with LLM models APIs (OpenAI/Anthropic); experience building and securing MCP servers at scale and designing end-to-end RAG systems; strong problem-solving, security, and architectural skills; additional familiarity with LLM guardrails, LangChain/LlamaIndex, and observability is a plus.
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
- Solid understanding of security best practices for backend systems, including authentication and data protection
- Nice-to-have: Experience with LLM guardrails, LangChain, LlamaIndex, LLM monitoring and observability
- Experience developing AI/ML technologies within large and business critical applications
- Building evaluation into LLM systems: eval harnesses, regression suites, LLM-as-judge, and offline/online quality metrics
- 30 days of paid vacation, training opportunities, employee programs, benefits, and modern office spaces
- Room for innovation in a high-growth environment with latest technologies and products
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