Senior Gen-AI Engineer

• Design, develop, and maintain scalable Python-based APIs and backend services using FastAPI and related frameworks.
• Build, deploy, and optimize production-grade LLM applications using providers such as OpenAI and Anthropic.
• Design and implement end-to-end RAG solutions, including vector databases, semantic search, retrieval optimization, and chunking strategies.
• Develop and manage secure, scalable MCP servers and AI infrastructure.
• Build and orchestrate multi-agent systems to automate complex workflows and business processes.
• Create, test, and refine prompts, agent instructions, and LLM interactions to improve solution quality and performance.
• Leverage AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot) to accelerate software delivery and engineering efficiency.
• Implement event-driven architectures, messaging systems, and real-time communication patterns.
• Monitor, troubleshoot, and optimize AI and backend systems for performance, reliability, scalability, and security.
• Collaborate with cross-functional teams to deliver innovative AI solutions and establish engineering best practices.

• 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) to write and refactor code, automate workflows, and optimize engineering processes.
• 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 skills:

• Experience with LLM guardrails
• Experience with LLM Frameworks (e.g. LangChain, LlamaIndex)
• Experience with 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.