Manish Gupta — AI Researcher

We are currently witnessing the most profound shift in enterprise technology since the cloud: the transition from Generative AI that talks to Agentic AI that acts. As a Lead AI Architect with over 9 years of experience in the trenches of software engineering and machine learning, I specialize in building the systems that make this transition possible. My passion lies not just in training models, but in orchestrating them building robust, autonomous Multi-Agent Systems that solve complex enterprise challenges with minimal human intervention. My journey has taken me from developing foundational OCR pipelines and Computer Vision systems to architecting sophisticated, context-aware agentic workflows using LangGraph, CrewAI, and Google ADK. I focus on the 'hard parts' of AI adoption: interoperability, governance, and production scalability. What I Deliver: I bridge the gap between cutting-edge AI research and production-grade software. I don't just build chatbots; I architect autonomous resource planning systems and enterprise web crawlers that understand context, execute multi-step reasoning, and deliver measurable ROI. Architectural Leadership: I design systems using the Model Context Protocol (MCP) to ensure secure, standardized connectivity between LLMs and enterprise data solving the 'silo' problem that plagues many AI initiatives. Operational Impact: I have a track record of transforming manual workflows into autonomous pipelines, recently reducing operational latency by 90% for critical business units. Holistic Strategy: From MLOps and AI Governance to team mentorship, I ensure that AI solutions are responsible, maintainable, and aligned with long-term business goals. Technical Focus: Agentic Orchestration: LangGraph (Stateful Flows), Google ADK (Agent Development Kit), CrewAI, ReAct Patterns, Multi-Agent Systems. Protocol & Integration: Model Context Protocol (MCP), APIs, Event-Driven Architecture, Chain-of-Thought (CoT). Generative AI: RAG (Retrieval-Augmented Generation), Fine-tuning (LoRA/QLoRA), Prompt Engineering, Gemini, Hugging Face. Cloud & MLOps: GCP Vertex AI, Azure AI Studio, Kubernetes, LangSmith, Guardrails AI, Docker, Terraform. Data Engineering: Vector Databases (Pinecone, Qdrant), Knowledge Graphs (Neo4j, FalkorDB). I am driven by the challenge of turning undefined problems into scalable, intelligent solutions. If you are looking to move your organization beyond AI hype and into the era of autonomous, value-generating agents, let’s connect.

Stackforce AI infers this person is a B2B SaaS expert specializing in AI-driven enterprise solutions.

Location: Delhi, India

Experience: 9 yrs 8 mos