GenAI Architect

Role Overview

We are seeking a GenAI Architect to join the Thermax AI team and lead the organization's next-generation AI architecture and innovation agenda. This role combines deepJob Title: GenAI Architect

Role Overview

We are seeking a GenAI Architect to join the Thermax AI team and lead the organization's next-generation AI architecture and innovation agenda. This role combines deep architecture expertise with technology strategy to build scalable enterprise AI capabilities, evaluate emerging technologies, and shape Thermax's long-term AI roadmap.

The focus is on defining future-ready AI architecture, building reusable platforms and accelerators, and enabling teams to deliver high-impact AI solutions. This is a hands-on role: you will not only define standards and patterns, but also build reference implementations, prototypes, and production-ready components alongside engineering teams. You will drive technical excellence, scalability, security, and innovation velocity across GenAI and agentic AI initiatives.

Key Responsibilities

AI Architecture Leadership

• Define and own enterprise-wide GenAI architecture principles, standards, and reference patterns.
• Design scalable, modular, and secure architectures for AI solutions across cloud and hybrid environments.
• Establish reusable AI frameworks, components, and accelerators to speed up solution development.
• Guide technical design decisions across Thermax AI Studio initiatives.
• Develop and maintain reference implementations (e.g., RAG patterns, agent frameworks, evaluation harnesses) to accelerate adoption.
• Review code and architecture for critical AI components and contribute directly to production code when needed.

Innovation & Emerging Technology Exploration

Continuously evaluate emerging technologies, including:

• Generative AI / Foundation Models
• Agentic AI and autonomous workflows
• Multimodal AI
• Open-source AI ecosystems
• Industrial AI applications
• Build rapid proofs of concept (POCs) and prototypes to validate new technologies.
• Recommend build vs. buy vs. partner decisions for strategic AI capabilities.
• Identify opportunities where AI can create competitive advantage for Thermax.

AI Platform & Technical Governance

• Define standards for LLMOps, model lifecycle management, observability, and evaluation.
• Establish responsible AI guardrails, security practices, and governance frameworks.
• Conduct architecture reviews and ensure technical quality across solutions.
• Drive platform decisions to ensure scalability, interoperability, and maintainability.

Technical Enablement & Solution Oversight

• Partner with product, engineering, and delivery teams to translate business needs into scalable AI solution blueprints.
• Provide architecture oversight and technical mentorship during solution implementation.
• Support critical technical problem-solving and unblock engineering teams when needed.
• Ensure solutions are production-ready and aligned with enterprise standards.

Capability Building & Thought Leadership

• Mentor engineers and data scientists on GenAI best practices.
• Build internal AI capability through reusable assets, standards, and knowledge sharing.
• Conduct trainings and knowledge-sharing sessions to build an internal community of AI champions.

Skills & Qualifications

• 10+ years of total experience, including 3+ years designing and deploying Generative AI / LLM-based solutions.
• Core technical skills:
• LLMs: GPT, Claude, Gemini, Llama, Mistral
• RAG & vector stores: Pinecone, Weaviate, ChromaDB, Azure AI Search
• Orchestration: LangChain, LlamaIndex, Semantic Kernel, AutoGen
• Cloud platforms: Azure OpenAI, AWS Bedrock, Google Vertex AI
• Programming: Python (required); experience with TypeScript/Java/Go is a plus
• Application engineering: building AI services/APIs (REST/gRPC), prompt/tooling interfaces, and integrations with enterprise systems
• Quality & reliability: automated evaluation, testing, observability, and cost/performance optimization for LLM-powered systems
• Proven experience designing scalable AI solutions, reusable frameworks, and cloud-native platforms.
• Strong stakeholder communication skills and ability to influence technical direction across teams.
• Experience in industrial, manufacturing, or IoT domains is a strong plus. architecture expertise with technology strategy to build scalable enterprise AI capabilities, evaluate emerging technologies, and shape Thermax's long-term AI roadmap.

The focus is on defining future-ready AI architecture, building reusable platforms and accelerators, and enabling teams to deliver high-impact AI solutions. This is a hands-on role: you will not only define standards and patterns, but also build reference implementations, prototypes, and production-ready components alongside engineering teams. You will drive technical excellence, scalability, security, and innovation velocity across GenAI and agentic AI initiatives.

Key Responsibilities

AI Architecture Leadership

• Define and own enterprise-wide GenAI architecture principles, standards, and reference patterns.
• Design scalable, modular, and secure architectures for AI solutions across cloud and hybrid environments.
• Establish reusable AI frameworks, components, and accelerators to speed up solution development.
• Guide technical design decisions across Thermax AI Studio initiatives.
• Develop and maintain reference implementations (e.g., RAG patterns, agent frameworks, evaluation harnesses) to accelerate adoption.
• Review code and architecture for critical AI components and contribute directly to production code when needed.

Innovation & Emerging Technology Exploration

Continuously evaluate emerging technologies, including:

• Generative AI / Foundation Models
• Agentic AI and autonomous workflows
• Multimodal AI
• Open-source AI ecosystems
• Industrial AI applications
• Build rapid proofs of concept (POCs) and prototypes to validate new technologies.
• Recommend build vs. buy vs. partner decisions for strategic AI capabilities.
• Identify opportunities where AI can create competitive advantage for Thermax.

AI Platform & Technical Governance

• Define standards for LLMOps, model lifecycle management, observability, and evaluation.
• Establish responsible AI guardrails, security practices, and governance frameworks.
• Conduct architecture reviews and ensure technical quality across solutions.
• Drive platform decisions to ensure scalability, interoperability, and maintainability.

Technical Enablement & Solution Oversight

• Partner with product, engineering, and delivery teams to translate business needs into scalable AI solution blueprints.
• Provide architecture oversight and technical mentorship during solution implementation.
• Support critical technical problem-solving and unblock engineering teams when needed.
• Ensure solutions are production-ready and aligned with enterprise standards.

Capability Building & Thought Leadership

• Mentor engineers and data scientists on GenAI best practices.
• Build internal AI capability through reusable assets, standards, and knowledge sharing.
• Conduct trainings and knowledge-sharing sessions to build an internal community of AI champions.

Skills & Qualifications

• 10+ years of total experience, including 3+ years designing and deploying Generative AI / LLM-based solutions.
• Core technical skills:
• LLMs: GPT, Claude, Gemini, Llama, Mistral
• RAG & vector stores: Pinecone, Weaviate, ChromaDB, Azure AI Search
• Orchestration: LangChain, LlamaIndex, Semantic Kernel, AutoGen
• Cloud platforms: Azure OpenAI, AWS Bedrock, Google Vertex AI
• Programming: Python (required); experience with TypeScript/Java/Go is a plus
• Application engineering: building AI services/APIs (REST/gRPC), prompt/tooling interfaces, and integrations with enterprise systems
• Quality & reliability: automated evaluation, testing, observability, and cost/performance optimization for LLM-powered systems
• Proven experience designing scalable AI solutions, reusable frameworks, and cloud-native platforms.
• Strong stakeholder communication skills and ability to influence technical direction across teams.
• Experience in industrial, manufacturing, or IoT domains is a strong plus.