Gen AI Architect

HCLTech; Pune District; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

HCLTech seeks a seasoned Generative AI Architect to lead enterprise-scale GenAI and Agentic AI initiatives, translating business goals into scalable, production-ready solutions. You will architect, design, and guide implementations across cross-functional teams, serving as the technical authority on AI architecture decisions.

This role requires deep GenAI experience, strong cloud and distributed systems knowledge, and leadership in governance, observability, and MLOps practices.

Qualifications

• Bachelor's or Master's degree in CS, AI, or related field.
• 5+ years as an Architect with large-scale enterprise system design.
• Strong knowledge of distributed systems, microservices, and API design.
• Experience with Azure OpenAI or cloud-native AI platforms is a plus.

Responsibilities

• Architect, design, and guide GenAI/Agentic AI implementations for Industry AI Solutions.
• Act as technical authority for AI architecture decisions within teams.
• Mentor developers and align AI efforts with business goals.

Skills

GenAI architecture

Cloud architecture

Distributed systems

Python

LLMs & GenAI

Prompt engineering

Education

Bachelor's or Master's in CS/AI

Tools

LangChain

LlamaIndex

AutoGen

CrewAI

Semantic Kernel

Pinecone / Weaviate

Job description

We are seeking a seasoned Generative AI Architect with a strong foundation in enterprise and system architecture, combined with significant depth and breadth in Generative AI (GenAI) and Agentic AI application development.

This is a senior cross-cutting role responsible for architecting, designing, and guiding the implementation of Industry AI Solutions.

The Generative AI Architect will serve as the technical authority for AI architecture decisions within their assigned teams, working alongside embedded GenAI Developers (who report to this architect for technical direction), traditional software engineers, and business stakeholders.

The architect bridges the worlds of robust enterprise system design and cutting-edge AI capabilities — translating business goals into scalable, secure, production-ready GenAI and Agentic AI solutions.

Mandatory Qualifications & Skills

Architecture & Engineering Foundation

• Bachelor's or Master's degree in Computer Science, Software Engineering, AI, Data Science, or a related field.
• Proven experience as a Solution Architect or Enterprise Architect (5+ years), with a track record of designing large-scale, production enterprise systems.
• Strong command of system design principles: distributed systems, microservices, event-driven architecture, API design, cloud-native patterns.
• Experience architecting across cloud platforms, with strong preference for Azure (Azure OpenAI, Azure AI Studio, Azure ML, Azure API Management).

Generative AI & Agentic AI Expertise

• Deep hands-on experience with LLMs and GenAI application development — including RAG architecture, LLM integration, prompt engineering, and chain-of-thought design.
• Proven experience architecting Agentic AI systems and multi-agent workflows using frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or equivalent.
• Strong understanding of LLM evaluation, observability, and LLMOps practices — including tracing tools, evaluation frameworks, and production monitoring.
• Experience with vector databases and embedding stores (Pinecone, Weaviate, Azure AI Search, FAISS, Chroma, or similar).
• Familiarity with LLM fine-tuning approaches (RLHF, PEFT, LoRA) and when to apply them versus prompt-based adaptation.

Programming & Technical Skills

• Strong Python proficiency — able to prototype, review, and guide implementation of GenAI components.
• Working knowledge of software engineering best practices: Git, CI/CD, automated testing, API design, containerization (Docker/Kubernetes).

Responsible AI & Governance

• Sound knowledge of Safe AI principles, AI security patterns, AI governance frameworks, and data privacy compliance.
• Ability to conduct AI risk assessments and embed governance into architecture decisions.
• Demonstrated ability to lead technical discussions and drive consensus across multi-disciplinary teams.
• Effective at communicating architecture decisions, trade-offs, and recommendations to both technical and executive audiences.
• Experience mentoring developers and guiding teams through complex AI implementation challenges.

Preferred Qualifications

• Experience leading AI architecture across multiple concurrent teams.
• Familiarity with MLOps tooling and platforms (MLflow, Azure ML Pipelines, Weights & Biases).
• Exposure to multimodal AI models (vision-language, speech-to-text, document AI).
• Experience with enterprise AI governance and compliance frameworks (EU AI Act, NIST AI RMF, or equivalent).
• Hands-on experience with AI-assisted development workflows and coding agents (e.g., GitHub Copilot, Cursor, or custom coding agents).
• Prior experience in a product architecture role delivering Industry AI Solutions at enterprise scale.