Principal AI Solutions Architect

Metatron Hr Solutions Coimbatore; Chennai District; On-site; INR 3,600,000 - 6,000,000; Full time

Job summary

Metatron HR Solutions Coimbatore is seeking a Senior Enterprise AI Architect in India to define and drive the enterprise AI architecture roadmap and AI transformation strategies aligned with business goals.

You will establish AI reference architectures, governance, and best practices, while guiding AI-first design across products and engineering teams, including work on RAG platforms, LLMs, and scalable AI platforms.

Qualifications

• Bachelor's or Master's degree in CS, AI, DS, Engineering, or related field.
• 12+ years of software engineering, architecture, and enterprise platform experience.
• 5+ years hands-on AI/ML architecture experience.
• Proven experience deploying enterprise AI solutions in production.

Responsibilities

• Define and drive enterprise AI architecture roadmap.
• Develop AI transformation strategies aligned with business objectives.
• Establish AI reference architectures, standards, governance models, and best practices.
• Drive adoption of AI-first design principles across products and engineering teams.

Skills

AI architecture

RAG platforms

Multi-Agent Systems

LLMOps

MLOps

AgentOps

Prompt Engineering

Knowledge graphs

Python

REST APIs

Education

Bachelor's or Master's in CS/AI/DS/Engineering

Tools

LangChain

LangGraph

LlamaIndex

Vector Databases

Pinecone

Weaviate

Chroma

Azure AI Search

OCI

Azure

AWS

GCP

Kubernetes

Containers

API Platforms

Event-Driven Architecture

Python

.NET

Distributed Systems

Job description

Key Responsibilities

• Define and drive the enterprise AI architecture roadmap.
• Develop AI transformation strategies aligned with business objectives.
• Establish AI reference architectures, standards, governance models, and best practices.
• Drive adoption of AI-first design principles across products and engineering teams.

Enterprise AI Strategy & Architecture

• Define and drive the enterprise AI architecture roadmap.
• Develop AI transformation strategies aligned with business objectives.
• Establish AI reference architectures, standards, governance models, and best practices.
• Drive adoption of AI-first design principles across products and engineering teams.

RAG & Knowledge Systems

• Design and implement enterprise-grade Retrieval Augmented Generation (RAG) platforms.
• Architect knowledge repositories, vector databases, semantic search systems, and enterprise knowledge assistants.
• Optimize retrieval quality, grounding accuracy, hallucination prevention, and response relevance.
• Build scalable knowledge management ecosystems leveraging structured and unstructured data.

Agentic AI & Multi-Agent Systems

• Design and implement autonomous AI Agent and Multi-Agent architectures.
• Build intelligent workflows capable of planning, reasoning, orchestration, execution, and decision support.
• Implement Agentic AI frameworks for software development, testing, support, customer operations, underwriting, claims processing, and business workflows.
• Establish agent governance, monitoring, security, and observability practices.

Large Language Models & Small Language Models

• Evaluate, benchmark, and optimize LLMs and SLMs across business use cases.
• Design hybrid AI architectures combining proprietary, open-source, and commercial models.
• Implement model selection, routing, orchestration, fine-tuning, and optimization strategies.
• Lead model performance, cost optimization, and inference efficiency initiatives.

AI Engineering & Platform Development

• Build scalable AI platforms supporting enterprise-wide adoption.
• Develop reusable AI services, frameworks, accelerators, SDKs, and APIs.
• Establish AI MLOps, LLMOps, and AgentOps practices.
• Design AI observability, monitoring, evaluation, and governance capabilities.

AI-Powered Engineering Transformation

• Drive AI-assisted software development initiatives.
• Implement AI-powered code generation, code review, testing, documentation, and DevOps solutions.
• Establish AI-driven SDLC workflows and engineering productivity frameworks.
• Partner with engineering leadership to build AI-enabled development organizations.

Innovation & Emerging Technologies

• Continuously evaluate emerging AI technologies and industry trends.
• Drive innovation programs, proofs of concept, and technology incubation initiatives.
• Provide thought leadership to executive management and engineering teams.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related discipline.
• 12+ years of software engineering, architecture, and enterprise platform experience.
• 5+ years of hands‑on AI/ML architecture experience.
• Proven experience designing and deploying enterprise AI solutions in production environments.

Mandatory Technical Expertise

Generative AI

• OpenAI
• Azure OpenAI
• Anthropic Claude
• Gemini
• Llama
• Mistral
• DeepSeek
• Open‑source foundation models

RAG Platforms

• LangChain
• LangGraph
• LlamaIndex
• Vector Databases
• Pinecone
• Weaviate
• Chroma
• Azure AI Search

Agentic AI

• Multi-Agent Systems
• AI Agent Frameworks
• Agent Orchestration
• Agent Planning & Reasoning
• Agent Memory Architectures
• Agent Governance

AI Platform Engineering

• LLMOps
• MLOps
• AgentOps
• Prompt Engineering
• Model Evaluation
• Fine‑Tuning
• Embeddings
• Knowledge Graphs

Cloud & Enterprise Platforms

• OCI
• Azure
• AWS
• GCP
• Kubernetes
• Containers
• API Platforms
• Event-Driven Architectures

Programming

• Python
• .NET
• REST APIs
• Microservices
• Distributed Systems

Preferred Qualifications

• Experience in Insurance, InsurTech, Financial Services, Healthcare, or Enterprise SaaS platforms.
• Experience building AI copilots, enterprise assistants, autonomous agents, and intelligent workflow platforms.
• Exposure to enterprise governance, security, compliance, and responsible AI frameworks.
• Experience leading AI transformation initiatives across large organizations.

Leadership Competencies

• Strategic thinking with hands‑on execution capability.
• Strong architecture and system design expertise.
• Exceptional communication and stakeholder management skills.
• Ability to influence engineering, product, and business leaders.
• Strong problem-solving and innovation mindset.
• Passion for mentoring and building AI capabilities across teams.