Gen AI Lead Engineer (W2 Only)

Job Title: Gen AI Developer - LeadLocation: 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.