
JD Role: AI Architect (Gen AI Specialist).
Experience: 12 to 17 Years.
Location: Bangalore & Pune.
Role Summary:
- Accountable for architecting and leading the delivery of AI-led AINext solutions built on Generative AI and Agentic AI.
- Owns solution architecture, model and framework selection, and technical quality for GenAI use cases, from design and prototyping through production deployment.
Key Responsibilities:
Solution Architecture & Design:
- Design end-to-end architecture for Generative AI and Agentic AI solutions on the AINext platform, covering LLM selection, RAG pipelines, agent orchestration, tool integration, and guardrails.
- Architect agentic and multi-agent workflows using frameworks such as LangChain, LangGraph, and Google ADK.
- Design backend and integration layers using Python and Java Spring Boot, exposing AI capabilities as secure and scalable services.
- Evaluate and recommend foundation models (for example Claude, Gemini, and OpenAI models) and deployment options for client problem statements.
- Design IDP (Intelligent Document Processing) solution architecture end to end, combining document ingestion, classification, OCR and layout-aware extraction, LLM-based extraction, validation, human-in-the-loop review, and downstream integration.
Technical Leadership & Quality:
- Provide technical leadership and mentorship to Gen AI engineers, Python developers, and technology leads.
- Establish standards for prompt engineering, agent design, evaluation, and deployment of GenAI solutions.
- Conduct design and code reviews, and ensure reliability, security, scalability, and performance of AI solutions.
- Troubleshoot and resolve technical issues in production AI systems.
Evaluation, Governance & Responsible AI:
- Define evaluation, observability, cost, and latency monitoring approaches for LLM and agent-based solutions.
- Assess ethical implications, data privacy, and security risks of GenAI deployments, and design appropriate guardrails.
Stakeholder Management & Pre-sales:
- Act as the primary technical contact for client architects and business stakeholders, and drive GenAI architecture workshops.
- Advise clients on GenAI and agentic AI use cases and provide feedback for the product roadmap.
- Partner with product architecture, data, engineering, and security teams.
- Support pre-sales activities by providing GenAI solution design, estimates, and expertise.
Required Qualifications and Skills:
- Strong hands-on experience architecting Generative AI solutions using LLMs, RAG, embeddings, vector databases, and prompt engineering.
- Experience building agentic AI solutions, including tool calling, multi-agent orchestration, memory, and planning, using LangChain, LangGraph, Google ADK, or similar frameworks.
- Experience with foundation models such as Claude, Gemini, and OpenAI models, and an understanding of their trade-offs.
- Strong programming skills in Python and Java Spring Boot, with experience in microservices and REST APIs.
- Experience with cloud platforms (AWS, Azure, or GCP), Docker, Kubernetes, and CI/CD.
- Strong understanding of data structures, databases (SQL and vector), and the AI project lifecycle.
- Understanding of AI security, data privacy, and responsible AI practices.
- Excellent communication skills and the confidence to convey technical advice and guidance to clients.
- Good to have: Understanding of end-to-end Intelligent Document Processing (IDP) solution architecture, including document ingestion, extraction, validation, and integration.
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