AI Solutions Architect – Enterprise AI & Agentic Platforms

Principal AI Solutions Architect – Enterprise AI & Agentic Platforms
Location
Chennai, India
Experience
8–18+ Years
We are seeking an exceptional Principal AI Solutions Architect to lead the design, implementation, and scaling of enterprise-grade AI, Generative AI, Agentic AI, and Intelligent Automation platforms that will drive the future of our engineering and product ecosystem.
Role Overview
This is a hands-on architecture and leadership role responsible for defining and executing Solartis’ enterprise AI strategy.
The ideal candidate will possess deep expertise in LLMs, SLMs, RAG architectures, AI Agents, Agentic AI systems, AI orchestration frameworks, enterprise AI governance, and production-scale AI platform development.
This role requires a rare combination of architecture leadership, hands-on engineering expertise, business understanding, and AI innovation capabilities.
The individual will work closely with Engineering, Product, Operations, Architecture, Customer Success, and Executive Leadership teams to transform traditional enterprise platforms into AI-powered intelligent systems.
Key Responsibilities
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
 Bachelor’s or Master’s 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.
Success Metrics
 Enterprise AI platform adoption.
 Successful deployment of RAG and Agentic AI solutions.
 AI-driven engineering productivity improvements.
 Reduction in operational effort through intelligent automation.
 AI governance and compliance maturity.
 Innovation velocity and business impact.
 Measurable ROI from AI initiatives.

Work arrangement
No