Mohan Kocherlakota

About Mohan Kocherlakota

AI Engineer specializing in multi-agent systems, RAG pipelines, and production-grade LLM architectures — with a Master\'s in Applied Machine Intelligence from Northeastern University (GPA 3.8).At Altimetrik, I design and deliver agentic AI systems that operate at enterprise scale. My work spans the full engineering and SDLC lifecycle: building multi-agent data pipelines with AI models (OpenAI, Claude) and open-source alternatives, architecting version-controlled RAG systems with vector databases, and implementing MCP-based autonomous deployment pipelines to GitHub — covering requirements analysis, SQL generation, automated test case creation, validation, and production deployment, all governed by human-in-the-loop approval workflows that keep enterprise teams in control.Beyond engineering, I am part of AI enablement at scale. I have trained 300+ engineers on topics ranging from GenAI fundamentals to advanced multi-agent architectures, evaluation frameworks, and observability — and have delivered enterprise Copilot L&D programs covering prompt engineering, custom MCP server development, and governance best practices.Prior to this role, I built LLM-based research orchestration systems at VesterAI and developed ML-driven risk analytics solutions at Traxidty. I hold certifications from OpenAI, AWS, and Hugging Face, and have participated in the OpenAI Global Codex Hackathon and been recognized as a semi-finalist at both the MIT Energy HackAIthon and MIT AI in Education Hackathon.I am driven by a single goal: making agentic AI practical, governable, and impactful in real enterprise environments.

Experience

1. Ai Software Engineer

   Altimetrik

   Jan 2026 — Present · Boston, MA, US

   Promoted to AI Engineer, expanding scope across enterprise AI enablement programs, Copilot governance initiatives, and internal GenAI platform development.AI ENABLEMENT | 300+ ENGINEERSPart of an end-to-end AI enablement program training 300+ engineers, spanning GenAI fundamentals through to advanced RAG, multi-agent systems, SDLC integration, evaluation frameworks, observability, and traceability.Designed and delivered hands-on learning and development programs covering real-world GenAI architecture patterns, enterprise SDLC deployment strategies, and production implementation best practices.ENTERPRISE L&D INITIATIVEDelivered a comprehensive Copilot L&D program covering prompt engineering, multi-agent usage, enterprise SDLC workflows, and Copilot governance best practices.Trained teams on custom MCP servers, agents.md and plan.md usage within a capstone-driven program designed around real enterprise deployment scenarios.INTERNAL PLATFORMS | BUILT FROM SCRATCHBuilt three end-to-end GenAI capability platforms aligned to enterprise SDLC and deployment standards- AI-powered engineering workflow automating ticket analysis, code implementation, and PR creation across Slack, Jira, GitHub, Snowflake, and via OpenAI Codex- Codex: Autonomous code deployment and testing platform- Copilot Training: Enterprise-scale Copilot learning platform.

Education

• Northeastern University

  Master's degree, Applied Machine Intelligence

• GITAM Deemed University

  Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering