AI Architect - Hybrid - Pune/Hyderabad/Bangalore

Department Icon Data Science Analytics & Machine Learning
Posted: 1 week ago
0-1 years
Pune, Maharashtra
Data Science Analytics & Machine Learning
work from office
Full Time
Closes 4 Jan 2027

Posted: 1 week ago
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Job Description

AI Architect

Pune, Hyderabad, Bangalore

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

Job description

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.

Skills

ImplementationLarge Language ModelAiMlLlmLlmsRagFine-tuningEmbeddingsTool CallingModel EvaluationAi Agents

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