Technical AI Architect – Generative AI

Experience: 1520 Years

Location: Chennai / Hybrid

Employment Type: Full-Time

Role Overview

We are looking for a highly experienced and visionary Technical AI Architectto lead enterprise-grade AI solution design and drive the next generation of GenAI innovation. The Technical AI Architect will be responsible for defining, designing, and governing scalable AI/ML and Generative AI architectures across enterprise applications and products. The role requires deep expertise in AI engineering, cloud platforms, distributed systems, LLM ecosystems, AI governance, and enterprise integration.

The ideal candidate should possess strong architectural leadership with hands-on experience in designing AI platforms, RAG pipelines, Agentic AI systems, AI orchestration frameworks, and scalable cloud-native solutions.

Key Responsibilities

• Design end-to-end enterprise AI and Generative AI architectures aligned with business goals.
• Lead architecture for:
• Large Language Model (LLM) applications
• Retrieval-Augmented Generation (RAG) systems
• Multi-agent AI systems
• AI copilots and enterprise virtual assistants
• AI workflow orchestration platforms
• Define scalable and secure AI infrastructure across cloud environments such as AWS, Azure, or GCP.
• Architect AI integration strategies with enterprise applications, APIs, databases, and third-party systems.
• Drive technical decisions on model selection, vector databases, orchestration frameworks, and deployment strategies.
• Establish AI governance, Responsible AI, security, compliance, and observability standards.
• Collaborate with engineering, product, DevOps, and business stakeholders to translate business requirements into scalable AI solutions.
• Provide architectural leadership and mentorship to AI engineers, solution architects, and development teams.
• Lead proof-of-concepts (POCs), technical discovery workshops, and enterprise AI transformation initiatives.
• Define best practices for MLOps, LLMOps, CI/CD pipelines, monitoring, and model lifecycle management.
• Ensure performance optimization, scalability, cost efficiency, and high availability of AI platforms.
• Stay updated with emerging AI trends including Agentic AI, multimodal AI, AI governance, and autonomous systems.

Required Technical Skills

Core AI & GenAI

• Strong expertise in:
• Generative AI
• LLMs
• NLP
• Deep Learning
• Machine Learning
• Prompt Engineering
• AI Agents & Agentic Frameworks
• Experience with:
• OpenAI
• Claude
• Gemini
• Llama
• LangChain
• LangGraph
• Semantic Kernel
• CrewAI / AutoGen
• Expertise in RAG architecture, embeddings, vector databases, and semantic search.

Cloud & Infrastructure

• Strong experience in AWS / Azure / GCP AI services.
• Expertise in Kubernetes, Docker, microservices, and distributed systems.
• Experience with scalable AI deployments and cloud-native architecture.

Data & Engineering

• Strong proficiency in Python and AI frameworks such as TensorFlow/PyTorch.
• Experience in API architecture, event-driven systems, and enterprise integrations.
• Knowledge of data engineering, ETL pipelines, and big data ecosystems.

DevOps & AI Operations

• Experience in:
• MLOps / LLMOps
• CI/CD
• Monitoring & observability
• AI governance
• AI security and compliance

Required Experience

• 1015 years of overall IT experience with significant exposure to AI/ML architecture.
• Minimum 2+ years in Generative AI or advanced AI solution architecture.
• Proven experience architecting enterprise-scale AI applications.
• Experience leading large technical teams and cross-functional initiatives.
• Strong exposure to enterprise software architecture patterns and cloud transformation programs.
• Experience in customer-facing technical consulting or solutioning roles is preferred.

Preferred Qualifications

• Bachelors/Masters degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• AI/Cloud certifications from AWS, Azure, Google Cloud, or equivalent
• Experience in enterprise consulting, SaaS platforms, or AI product companies.
• Exposure to Responsible AI frameworks and AI governance models.

Soft Skills

• Strong leadership and stakeholder management skills.
• Excellent problem-solving and strategic thinking ability.
• Strong communication and presentation skills.
• Ability to work in fast-paced innovation-driven environments.
• Passion for emerging AI technologies and continuous learning.