Position: Architect – AI/ML (Gen AI)
Purpose of the Position:
The purpose of the AI/ML Architect (Generative AI) role is to design, build, deploy, and operate production-grade AI systems with a strong focus on large language models (LLMs), generative AI applications, and intelligent automation.
Location: Chennai/Bangalore/Pune/Nagpur
Type of Employment: Full-time
Key Result Areas (KRAs):
Technical Leadership & Architecture Ownership
- Own the end-to-end technical architecture for enterprise GenAI, LLM, RAG, and LLMOps solutions.
- Drive architectural decisions including model selection, deployment approaches, build-vs-buy evaluation, and platform strategy.
- Review, validate, and approve solution designs, codebases, prompts, and evaluation frameworks.
- Define reference architectures, reusable patterns, and engineering standards for GenAI implementations across teams.
Enterprise GenAI Solution Delivery
- Design, own, and deliver production-grade generative AI systems using state-of-the-art techniques.
- Ensure solutions meet performance, scalability, cost-efficiency, security, and business impact expectations.
- Optimize models and pipelines for accuracy, latency, reliability, and enterprise-scale deployment.
LLM & Application Development
- Design and implement LLM-driven applications using foundation models and APIs.
- Own prompt engineering strategies, system prompts, evaluation pipelines, and inference optimization.
- Optimize solution cost, latency, and quality across environments.
Retrieval-Augmented Generation (RAG)
- Architect and build RAG pipelines integrating enterprise knowledge sources with LLMs.
- Work with vector databases, embedding models, and semantic search solutions.
- Define strategies to evaluate, monitor, and reduce hallucination risks.
AI Platformization & LLMOps
- Operationalize GenAI systems using CI/CD pipelines and MLOps/LLMOps best practices.
- Own monitoring for performance, drift, hallucinations, cost, and reliability.
- Implement versioning, rollback, observability, and controlled rollouts for GenAI solutions.
Stakeholder & Business Advisory
- Act as a trusted technical advisor to business, leadership, and client stakeholders for GenAI initiatives.
- Translate business problems into GenAI solution strategies and technical roadmaps.
- Communicate technical trade-offs, risks, feasibility, and ROI considerations effectively to decision-makers.
Mentorship & Capability Building
- Mentor and guide junior AI/ML engineers and data scientists.
- Conduct design, code, and prompt reviews to maintain high-quality engineering standards.
- Contribute to building organizational GenAI capability through documentation, best practices, and knowledge-sharing initiatives
Governance, Security & Responsible AI
- Own and enforce Responsible AI, data privacy, and security standards for GenAI solutions.
- Design and implement safeguards to mitigate hallucinations, bias, misuse, and data leakage.
- Ensure solutions comply with enterprise policies, industry regulations, and ethical AI principles.
