Job Title: Gen AI Developer - Lead
Location: Remote, US
Mode: Contract
Core Responsibilities
• Collaborate with product, engineering, security, and business stakeholders.
• Drive adoption of AI across engineering teams.
• Establish governance, security, and responsible AI practices.
• Influence senior leadership through data-driven insights.
• Prior experience leading teams and large-scale engineering initiatives.
• Manage delivery plans, roadmaps, and stakeholder communication.
• Design, develop, and deploy production-grade AI Agents and multi-agent systems.
• Build and maintain complex workflows using LangGraph.
• Develop and integrate MCP (Model Context Protocol) servers/clients and A2A (Agent-to-Agent) communication.
• Build scalable, distributed AI systems with a focus on performance, reliability, and fault tolerance.
• Develop RAG pipelines, context engineering strategies, and prompt engineering best practices.
• Implement AI evaluation frameworks (quality, hallucination, regression, latency, etc.).
Must Have
• 8+ years of software engineering experience with 3+ years in Generative AI/LLM applications.
• 3+ years of experience with leading teams and large-scale engineering initiatives.
• Strong Java and Python development experience (Mandatory).
• Hands-on experience with LangChain and LangGraph.
• Experience building AI Agents and multi-agent workflows.
• Experience with Kubernetes and Azure cloud services.
• Experience with Azure OpenAI (or OpenAI APIs).
• Strong understanding of Prompt Engineering and Context Engineering.
• Experience implementing RAG pipelines.
• Experience with one or more Vector Databases: Pinecone, Weaviate, FAISS, or OpenSearch.
• Experience with MCP (Model Context Protocol) and/or A2A integrations.
• Knowledge of AI evaluation techniques and frameworks.
• Understanding of distributed systems, scalability, caching, retries, and asynchronous programming.
• Experience with Git, Docker, and GitHub Actions/CI-CD.
Nice to Have
• Experience with Node.js (Optional).
• Experience with FastMCP, FastAPI, Pydantic, Angular.
• Knowledge of GraphRAG and Knowledge Graphs.
• Experience with Semantic Kernel, LlamaIndex, CrewAI, or AutoGen.
• Familiarity with Redis, Kafka, RabbitMQ, or event-driven architectures.
• Experience with AI benchmarking tools such as Ragas or DeepEval.
• Exposure to OpenSearch hybrid search and HNSW indexing.
• Experience mentoring engineers and leading technical design discussions.
• Familiarity with Harness or other deployment/release engineering tools.
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