As an AI Architect at Building Automation (BA), you will be responsible for designing, developing, and implementing artificial intelligence solutions that address BA business challenges and drive innovation. This role involves collaborating with stakeholders to define AI architecture, strategies, selecting appropriate technologies, and ensuring alignment with business objectives. The AI Architect ensures that solutions are scalable, secure, and aligned with organizational goals. You will have an impact on organization's ability to adapt, scale, and thrive in an ever-evolving technological landscape.

Technical & Architectural Leadership

• Design and deliver scalable AI/ML systems, including data pipelines, model lifecycle management, GenAI, agentic AI, and inference services.
• Direct strategy for AI and agentic AI architecture, covering multi-agent frameworks, orchestration, reasoning pipelines and governance.
• Lead key strategies and define Buy vs. build vs Tune Open-source models (like Llama 3)
• Lead BA base model approach including fine tune selection (Full tuning) and RAG
• Plan and launch AI platforms that meet standards for scalability, reliability, security, safety, and responsible AI.
• Set architectural standards and best practices for AI/ML platforms, LLM/GenAI, and agentic AI ecosystems.
• Oversee AI solution design to ensure it aligns with Forge.AI, data strategy, RAI, AI Governance and regulatory requirements.

AI/ML Architecture roadmap & Execution

• Work with product, data science, and business leaders to define key AI/ML opportunities and turn them into actionable engineering plans.
• Advise teams on model selection, training, feature engineering, and MLOps for robust, ethical, scalable solutions.
• Assess and adopt new AI technologies, frameworks, and tools with a pragmatic, results-focused approach.
• Work with Data Science, MLOps, Cloud Engineering, Security, and Business Units to define and implement top-level AI architecture aligned with business goals.

QUALIFICATIONS AND TECHNICAL SKILLS

• Bachelor’s or Master’s degree in Computer Science, Engineering, AI, Data Science, or related field
• Overall 14+ years of experience including 5 or more years of experience in AI architecture
• Work experience with AI frameworks and tools such as TensorFlow, PyTorch, or similar
• Proven technical experience in architecting solutions for machine learning, LLM/GenAI platforms and autonomous multi-agent systems using frameworks like LangGraph to solve complex, multi-step problems
• LLM/SLM Knowledge: Deep expertise in transformer architecture, context window management, model optimization/customization, Fine tuning (SFT, PEFT) and token budgeting for models like GPT-4, Llama 3, and specialized SLMs (e.g., Phi, Mistral 7B)
• Agentic Frameworks: Proficiency with orchestration tools such as LangChain, Semantic Kernel, or LangGraph for managing stateful, multi-agent loops
• Domain Modeling & Knowledge Graphs: Proficiency in mapping complex industrial hierarchies (e.g., HVAC systems, factory floor layouts) into Knowledge Graphs to provide LLMs with structured, relational context
• Multimodal RAG for Industrial use cases: Ability to design RAG pipelines that gather and retrieve data from engineering drawings, data sheets and technical manuals using vision-language models. 
• AI Governance: Establish standards, safety measures, and ethical guidelines to avoid hallucinations and adversarial prompts
• Proven leadership skills with the ability to inspire and mentor architects, engineers, and planners supporting AI initiatives
• Strong background in project leadership, steering large-scale or complex AI architecture programs from conception to implementation
• Deep understanding of cloud-native architecture (preferably Azure), security frameworks, data platforms, and modern AI/ML deployment patterns.

 WE VALUE

• Ability to build and maintain strong relationships with Architects, data science, engineering, security, and executive stakeholders
• Strategic mindset and an ability to translate business objectives into actionable AI platform and architecture strategies
• Experience with agentic AI frameworks, vector databases, orchestration layers, or autonomous workflow systems
• Passion for innovation and navigating the rapid evolution of AI technologies while maintaining stability and governance
• Familiarity with data monetization, secure data sharing, and analytics in hybrid platforms