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Senior Agentic AI Solution Architect

  • Source: LinkedIn
  • ThinkWise Consulting LLP
  • On-site
  • Hyderabad
  • Full-Time
  • Senior

Job Description

Job Location: Remote — Hyderabad, Indore . Ahmedabad

Experience: 10+ Years

Role Type: Hands-on technical architect — not a delivery or engagement management role

About the Role:

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.

You will define the architecture from first principles, working directly with the client’s senior engineering

leadership.

The platform has two layers: an advisory layer that turns enterprise signals into root-cause analysis,

backlog mapping, and next-best-action recommendations; and an execution layer that models

requirements, self-validates solutions pre-deployment, and orchestrates readiness and go-live.

The defining constraint is governed autonomy — the client operates in a regulated trust-and-

compliance domain, so every autonomous decision must be auditable, factually grounded, and safe.

Key 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.
  • 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.
  • Strong 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.

Education

  • Bachelor’s or master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field

Skills

  • agentai
  • guardrails
  • LangGraph
  • LangChain
  • Python
  • Java
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