Description : 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.

Essential Skills :

- Strong proficiency in Python with hands-on experience using PyTorch, TensorFlow, Keras, and related AI/ML frameworks.

- Deep expertise in deep learning techniques including transformer-based architectures, GANs, and neural networks.

- Experience training, fine-tuning, and evaluating large-scale AI and GenAI models.

- Strong understanding of LLMs, APIs, context management, token optimization, and enterprise integration.

- Hands-on experience designing and deploying RAG architectures using vector databases and embeddings.

- Strong software engineering skills with experience building scalable APIs and services.

- Solid understanding of MLOps and LLMOps practices including CI/CD, monitoring, observability, and cost management.

- Ability to evaluate, select, and define appropriate models, tools, and architectures based on business needs, cost, performance, and risk.

- Strong analytical and problem-solving skills with ownership-driven decision-making.

Desirable Skills :

- Experience deploying AI workloads on cloud platforms such as AWS, Azure, or GCP.

- Working knowledge of NLP techniques including text classification, summarization, and conversational AI.

- Exposure to agentic AI frameworks such as LangChain, LangGraph, CrewAI, or Semantic Kernel.

- Experience with FastAPI or Flask for serving AI models.

- Familiarity with Docker and Kubernetes for scalable deployments.

- Exposure to cloud-native GenAI services such as Azure AI Foundry, AWS Bedrock, or Vertex AI.

Qualifications :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

- Certifications (Preferred) : Relevant certifications in AI/ML or cloud platforms (e.g., TensorFlow Developer, AWS/Azure ML certifications).

- Experience :10-15 years of experience in AI and machine learning, with demonstrated ownership of enterprise-scale generative AI solutions.

Qualities :

- Demonstrates technical leadership, ownership mindset, and the ability to influence decisions without formal authority.

- Approaches problems logically and systematically with persistence and accountability.

- Able to consult, document, and present technical decisions persuasively.

- Comfortable working in self-organized, cross-functional, and client-facing environments.

- Adapts quickly based on feedback, peer reviews, and evolving requirements.

- Strong communication skills with high proficiency in written and spoken English.