Job highlights

- Deep multi-agent orchestration expertise: planning,reasoning loops,tool use,memory,and agent collaboration. .

Strong RAG and knowledge architecture: embedding strategy,hybrid / semantic retrieval,vector stores,and grounding. . Hands-on experience with agentic frameworks (LangGraph,LangChain,or equivalent) and MCP or comparable tool-access layers.

- Required Skills Experience

Job Summary

We are looking for an experienced Senior Agentic AI Solution Architect to serve as technical design partner for a strategic enterprise client building a greenfield, production-grade multi-agent AI platform.

Responsibilities

Architecture Ownership

- Own end-to-end architecture: ingestion, knowledge/retrieval, agent reasoning, tool access, and governance.

- Design the knowledge lake across telemetry, voice-of-customer signals, CRM, backlog systems, documents, and repositories.

- Architect the MCP gateway, registry, servers, and connectors for governed tool and data access.

Multi-Agent System Design

- Design the multi-agent reasoning core: planner/re-planner, reasoning loops, memory, and agent collaboration.

- Define orchestration, planning, reasoning, and autonomous workflow architectures.

- Architect solutions utilizing LLMs, RAG, knowledge systems, vector databases, and semantic search.

Governance Evaluation

- Build governance as a first-class layer: audit trails, grounding, guardrails, human-in-the-loop, and graceful degradation.

- Establish AI governance, security, explainability, observability, and Responsible AI standards.

- Define the evaluation harness, quality metrics, and measurable baselines.

Delivery Technical Direction

- Drive an end-to-end pilot on a real use case before scaling.

- Set technical direction for the offshore delivery pod.

- Create architecture blueprints, reference implementations,



and reusable frameworks; guide engineering teams through implementation and technology decisions.

Required Skills Experience

- 10+ years in software engineering/architecture, including 3+ years hands-on with agentic or multi-agent LLM systems in production.

- Proven greenfield architecture ownership on a complex, ambiguous system.

- Deep multi-agent orchestration expertise: planning, reasoning loops, tool use, memory, and agent collaboration.

- Strong RAG and knowledge architecture: embedding strategy, hybrid/semantic retrieval, vector stores, and grounding.

- Hands-on experience with agentic frameworks (LangGraph, LangChain, or equivalent) and MCP or comparable tool-access layers.

- Demonstrated AI safety and evaluation work: hallucination mitigation, guardrails, and evaluation harnesses.

- Robust Python and/or Java development experience, with API-first and microservices-based architecture background.

- Exceptional client-facing communication - able to hold your own with a senior technical executive.

- Still hands-on: writes code, builds prototypes, debugs real systems.

Preferred / Good to Have

- Regulated or compliance-sensitive domain experience (privacy, GRC, security, financial services, healthcare).

- Consulting or client-embedded background.

- Experience with distributed onshore/offshore delivery models.

- Experience with cloud AI platforms such as Azure AI Foundry, AWS Bedrock, or Google Vertex AI.

- Familiarity with MLOps/LLMOps practices and model evaluation frameworks.

Education

- Bachelor s or master s degree in Computer Science, Engineering, Artificial Intelligence, or a related field (or equivalent practical experience).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Agentic AI Solution Architect (Indore)
🏢 Thinkwise Consulting
📍 Indore