AI Solution Architect – Agentic AI & Engineering Transformation

Position Summary:

Seeking a highly experienced AI Architect to lead the design, adoption, and scaling of AI-driven Software Development Lifecycle (SDLC) practices and Agentic AI solutions across the organization.

Why this Role is important

This is not a traditional architecture role. You will be at the forefront of transforming a large-scale engineering organization into an AI-First Delivery Enterprise, defining how software is designed, built, tested, and operated in the age of Generative AI and Agentic AI.

You will have the opportunity to:

• Shape the organization's enterprise AI strategy and engineering future state.
• Build and scale Agentic AI capabilities from the ground up.
• Define next-generation AI-driven SDLC practices.
• Work on real-world AI transformation initiatives rather than isolated proofs of concept.
• Partner with senior architects, engineering leaders, business executives, and technology vendors.

Location: Offshore – India
Experience: 12+ years overall; strong recent GenAI / Agentic AI architecture experience
Domain: Banking & Financial Services – Cards, Payments, Customer Service, Collections, Identity, Loyalty, Digital Servicing

Key Responsibilities

• Define AI target architecture and adoption roadmap
• Drive AI across requirements, design, coding, testing, documentation, release and support
• Design Agentic AI solutions using agents, MCP/API integrations and human-in-the-loop controls
• Establish reusable patterns for LLMs, RAG, agents, security, evaluation and observability
• Identify and prioritize AI use cases across DSS, Pega, Collections, Batch and Digital
• Apply AI to legacy analysis, modernization, testing and migration acceleration
• Enable AI-assisted incident triage, RCA, knowledge retrieval and operational automation
• Drive PoC Pilot Production with security and governance controls
• Measure productivity improvement and translate it into validated capacity / cost savings
• Mentor engineering teams and create reusable accelerators
• Establish AI adoption frameworks, governance models, and implementation standards.
• Evaluate emerging AI technologies, frameworks, and platforms.
• Provide technical guidance to engineering teams, architects, and product owners.

Core Skills

Technical skills:

1. AI & Generative AI : Strong experience in:

• Large Language Models (LLMs)
• GPT-based architectures
• OpenAI ecosystem
• Azure OpenAI
• Anthropic Claude
• Gemini
• Prompt Engineering
• RAG architectures
• Vector databases
• Embedding models
• Fine-tuning concepts
• AI evaluation frameworks

 2. Agentic AI: Hands-on experience with:

• Multi-agent architectures
• Autonomous workflow agents
• AI orchestration frameworks
• Agent lifecycle management
• Planning and reasoning systems
• Tool integration frameworks
• Human-in-the-loop patterns
• MCP Server

 3. Preferred exposure to below AI platforms/framework:

• LangGraph 
• AutoGen
• LangChain
• CrewAI
• Microsoft Copilot Studio
• Azure AI Foundry

 4. Software Engineering: Strong understanding of:

• Agile delivery
• Microservices
• Event-driven architecture
• SDLC methodologies

 5. Cloud & Platforms: Experience with:

• Microsoft Azure
• AWS
• Google Cloud
• AI services and cloud-native architecture
• Devops pipeline for both Brownfield and GreendField applications

Leadership Skills

• Ability to influence senior leadership and engineering organizations
• Executive stakeholder management
• Team mentoring and coaching
• Strong communication and presentation skills