AI Architect - Hybrid - Pune/Hyderabad/Bangalore

iitjobs, Inc.; Pune District; Hybrid; INR 3,000,000 - 6,000,000; Full time

Job summary

iitjobs, Inc. is seeking a hands-on AI Architect to design and guide secure, scalable AI solutions across enterprise workflows. You will connect business needs with practical architecture, advise on model choices, and support from discovery to production adoption while collaborating with Product Owners.

The role requires ownership of production AI/ML, strong understanding of LLM behavior, and hands-on experience with agents, RAG pipelines, and tool orchestration in enterprise environments.

Qualifications

• Ownership of production AI or ML solutions and enterprise integrations.
• Understanding of large language model behavior, prompting and evaluation.
• Hands-on experience with tool-enabled agents and RAG pipelines.

Responsibilities

• Architecture and strategy: define target architectures and phased delivery plans for AI solutions.
• AI agents and orchestration: design agents with tool calling and workflow orchestration.
• RAG and enterprise knowledge: architect document ingestion, embeddings, vector search, and grounded responses with source citations.

Skills

Enterprise architecture

LLMs

AI systems

Prompting

Agent orchestration

Tools

Vector databases

Agent frameworks

Model gateways

Job description

Hybrid (need to travel for co-location as and when required)

We are looking for a hands-on AI Architect for a Leading Global Company that provides enterprise technology solutions. Who can design and guide the delivery of secure, scalable AI solutions across enterprise workflows. Who can connect defined business needs with practical architecture, advise teams to choose appropriate models and platforms, and support taking solutions from discovery through production adoption while working closely with Product Owners.

Key responsibilities:-

Architecture and strategy. Assess business workflows, data readiness and existing systems. Define target architectures and phased delivery plans, choosing among rules, traditional ML, RAG and agent-based approaches according to the use case.

AI agents and orchestration. Design agents with tool calling and workflow orchestration. Experience with agent orchestration frameworks, vector databases, enterprise search, model gateways and LLM evaluation or observability tools.

RAG and enterprise knowledge. Architect document ingestion, parsing, chunking, embeddings, vector and hybrid search, reranking and grounded responses with source citations. Preserve source permissions and keep knowledge current.

Required experience and skills:-

Enterprise architecture delivery. Demonstrated ownership of production AI or ML solutions and enterprise integrations, including architecture decisions, implementation guidance and operational outcomes.

LLMs and traditional AI. Strong understanding of large language model behavior, prompting, context limits, embeddings, model evaluation and fine-tuning trade-offs, alongside established ML methods and their lifecycle.

Agents and RAG. Hands-on experience implementing tool-enabled agents and RAG pipelines. Ability to explain retrieval quality, grounding, tool execution, memory boundaries, failure modes and appropriate human intervention.