Senior Solution Architect – AI Technologies

Title: Senior Solution Architect – AI Technologies

Experience: 15-20 Years

Role: Solution Architect – AI Technologies / GenAI Architect / Enterprise AI Architect

We are seeking an experienced Solution Architect – AI Technologies with 15-20 years of overall IT experience and deep expertise in designing, architecting, and delivering enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will possess strong technical leadership skills, hands-on experience with modern AI frameworks, and the ability to translate business requirements into scalable AI-driven solutions.

This role requires expertise in Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, Multi-Agent Systems, LangGraph, Model Context Protocol (MCP), Large Language Models (LLMs), Python, PySpark, Cloud AI Services, and Enterprise Data Platforms .

Key Responsibilities

AI Solution Architecture

• Define and lead enterprise AI architecture strategy aligned with business objectives.
• Design scalable and secure AI/GenAI solutions leveraging LLMs, RAG frameworks, and Agentic AI architectures.
• Create end-to-end solution blueprints covering data ingestion, knowledge retrieval, orchestration, model interaction, observability, and governance.
• Develop architecture roadmaps for AI modernization initiatives.

Generative AI & Agentic AI

• Design and implement enterprise-scale RAG systems using vector databases and semantic search technologies.
• Architect multi-agent and autonomous agent workflows using frameworks such as LangGraph and Agentic AI platforms.
• Develop AI solutions utilizing MCP (Model Context Protocol) for tool integration and contextual orchestration.
• Establish best practices for prompt engineering, agent collaboration, memory management, and workflow orchestration.
• Drive adoption of AI-powered automation and intelligent decision-making systems.

Data & Engineering Leadership

• Design scalable data pipelines using Python, PySpark, and cloud-native technologies.
• Architect enterprise knowledge management solutions supporting AI applications.
• Define data governance, security, privacy, and compliance frameworks for AI systems.
• Collaborate with data engineering teams to optimize AI data platforms.

Cloud & Platform Architecture

• Architect AI solutions on GCP cloud platforms.
• Evaluate and integrate AI services, vector databases, model serving platforms, and observability tools.
• Ensure scalability, reliability, performance, and cost optimization of AI solutions.
• Drive MLOps and LLMOps adoption across development teams.

Stakeholder Management

• Engage with business stakeholders, product owners, and leadership teams to define AI strategy and roadmap.
• Conduct solution workshops, architecture reviews, and technical governance sessions.
• Mentor architects, developers, and AI engineers on enterprise AI best practices.
• Support presales activities, client presentations, and AI transformation initiatives.

Required Skills & Qualifications

Experience

• 15-20 years of overall IT experience.
• Minimum 5+ years in AI/ML and Generative AI solution architecture.
• Proven experience leading enterprise-scale architecture programs.

AI & GenAI Technologies

• Strong expertise in:
• Generative AI
• Large Language Models (GPT, Claude, Llama, Gemini, etc.)
• Retrieval-Augmented Generation (RAG)
• Agentic AI Systems
• Multi-Agent Architectures
• LangGraph
• LangChain
• Model Context Protocol (MCP)
• AI Orchestration Frameworks
• Prompt Engineering

Programming & Data Engineering

• Expert-level proficiency in Python.
• Strong hands-on experience with PySpark.
• Experience with distributed data processing and analytics platforms.
• Knowledge of data modeling, ETL, and data governance.

AI Infrastructure & Platforms

• Experience with:
• Vector Databases (Pinecone, Weaviate, ChromaDB, Azure AI Search, etc.)
• Knowledge Graphs
• LLMOps/MLOps Platforms
• AI Monitoring and Evaluation Frameworks
• API Design and Microservices Architecture

Cloud Platforms

• Strong experience in Azure, AWS, or Google Cloud Platform.
• Knowledge of cloud-native AI services and enterprise deployment patterns.

Preferred Qualifications

• Experience in Automotive, Manufacturing, Supply Chain, or Engineering domains.
• Exposure to enterprise platforms such as PLM or Digital Engineering ecosystems.
• Experience implementing AI governance, responsible AI, and security frameworks.
• AI/Cloud certifications from Google Cloud.

Leadership Expectations

• Define enterprise AI reference architectures.
• Lead technical architecture reviews and solution decisions.
• Provide thought leadership on emerging AI technologies and industry trends.
• Drive innovation initiatives leveraging GenAI and Agentic AI capabilities.
• Mentor and guide cross-functional teams in AI solution delivery.

Nice-to-Have Skills

• GraphRAG
• CrewAI
• AutoGen
• Semantic Kernel
• Azure OpenAI
• Databricks
• MLflow
• Kubernetes
• Neo4j Knowledge Graphs
• OpenTelemetry
• AI Governance Frameworks