- Location
- Bengaluru, KA,IN, IN
- Type
- Full-time
- Department
- IT
- Education
- Master
- Source
- Eightfold
Description
Lead by doing — personally design, prototype, and build core platform components while guiding the India-based engineering team through hands-on technical direction, code reviews, and example. Drive AI solution architecture across the AI Hub — designing reusable, scalable patterns for agentic, RAG, and orchestration-based solutions on the shared platform. Build and maintain the integration “plumbing” — connectors to enterprise applications, Model Context Protocol (MCP) servers, APIs, and data services that link the AI platform to Lam's business systems. Extend and operationalize enterprise productivity tools — making Microsoft 365 Copilot and Copilot Studio more capable and widely adopted across the larger user community through custom connectors, agents, and plugins. Partner with product managers, AI governance, and the full-stack team to translate business problems into production-grade AI solutions. Establish engineering best practices for quality, security, observability, and cost-efficiency across the team's deliverables. Collaborate across US and India teams to ensure a cohesive, follow-the-sun delivery model. Bachelor's or Master's in Computer Science, Engineering, or a related field, with 8+ years of deep, hands-on software/AI engineering experience, including time as a technical lead who delivers through direct contribution. Proven experience architecting and delivering enterprise-scale AI/GenAI solutions — including agentic frameworks, retrieval-augmented generation (RAG), and orchestration. Hands-on expertise building integrations and connectors to enterprise applications, with working knowledge of Model Context Protocol (MCP), APIs, and authentication patterns. Experience extending Microsoft productivity platforms — Microsoft 365 Copilot, Copilot Studio, or Power Platform — for enterprise users. A lead-by-doing mindset — comfortable being the most technical person on the team, setting direction by writing code and architecture, and mentoring engineers as a peer rather than a hands-off manager. Experience developing on cloud platforms such as Azure and/or Databricks. Familiarity with GenAI orchestration frameworks (e.g., LangChain, LangGraph) and agent communication standards (e.g., MCP). Experience with enterprise data integration, data engineering, and API/connector development. Background working in a global, distributed (US/India) delivery model. Strong communication and stakeholder-management skills across technical and business audiences
