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.

Work arrangement
No