AI Development Lead/Architect (AI Innovation Program Manager)

Responsibilities About the AI Innovation Lab The AI Innovation Lab enables rapid testing of new AI ideas to validate their technical feasibility and business value. A critical input into this process is strong outside‑in research—understanding market trends, emerging technologies, competitor moves, and evolving best practices to ensure the Lab’s backlog and POCs are forward‑looking, relevant, and strategically aligned. Role Overview : This role is the senior-most technical authority for the AI Innovation Lab, responsible for designing, building, and scaling enterprise-grade AI solutions with a focus on GenAI, agentic architectures, and intelligent automation. Leads multi-disciplinary engineering teams to deliver production-ready AI capabilities at startup speed, ensuring technical feasibility, scalability, and integration with enterprise systems. Requires deep hands-on expertise across GenAI, ML, architecture, and enterprise systems Must deliver working solutions in weeks, as an extension to research and prototypes Balances cutting-edge experimentation with production-grade rigor Designs for reuse and orchestration of digital workers/agents at scale Experience with LLMs, AI tools and techniques to experiment with use cases within the Innovation Lab with speed What You’ll Do AI Solution Architecture & Build Design and deliver end-to-end AI solutions, including: GenAI / LLM-based applications Agentic workflows and orchestration layers ML + analytics integration Define scalable architectures aligned to enterprise systems and data environments Rapid Prototyping & POC Delivery Lead engineering teams through rapid POC development cycles (weeks) Convert business problems into working AI solutions with measurable outputs Ensure solutions meet technical feasibility thresholds for scaling Platform & Reusability Strategy Build reusable: AI components Data pipelines Agent frameworks Enable cross-use-case reuse and enterprise scalability Engineering Leadership Lead distributed teams (onshore/offshore) across: AI/ML engineers Data engineers Full-stack developers Establish best practices across: MLOps / LLMOps DevOps Strong understanding of the importance of engineering resiliency, within the AI ecosystem. Responsible AI Integration & Production Readiness Ensure seamless integration with: Enterprise data platforms APIs, and legacy systems Identify risks, dependencies, and constraints early Prepare solutions for transition to execution factory / production environments Qualifications Who You Are Bringing a Bachelor’s or Master’s degree - B.E. / B.Tech / M.S. / M.Tech / MCA degree in Computer Science, Technology, Engineering, Mathematics or a related subject area 12–18+ years in AI/ML, data engineering, and enterprise architecture Deep hands-on expertise in: GenAI / LLM frameworks Cloud platforms (AWS/Azure/GCP) API-based architecture and microservices Proven track record delivering AI solutions in production environments Skills That Will Help You Stand Out Combines research-level AI knowledge with enterprise delivery discipline Proven ability to deliver agent-based and GenAI solutions at scale Strong leadership of multi-POD, cross-functional engineering teams onshore and offshore Ability to translate ambiguous business problems into technical systems quickly Is able to negotiate senior business, technology and product management stakeholders, to socialize the POC outcomes, and ensure the final business needs are met. Additional Information Why Join the AI Innovation Lab? Work across a diverse set of high‑impact AI ideas rather than a single long‑lived pipeline. Operate in a fast‑paced, learning‑first environment that values pragmatism over perfection. Directly influence how quickly AI ideas move from concept to validated proof points. Our Engineering Culture Through our Agile/Lean DevOps environment dedicated to delivering valuable solutions, we’ve fostered a culture of innovation and experimentation across our development teams. As a customer-focused organization, we work closely with our end users and product owners to understand and rapidly respond to emerging business needs. Collaboration is embedded into everything we do – from the products we develop to the quality service we provide. We’re driven by the belief that diversity of thought, background, and perspective is critical to creating the best products and experiences for our customers. About the AI Innovation Lab The AI Innovation Lab enables rapid testing of new AI ideas to validate their technical feasibility and business value. A critical input into this process is strong outside‑in research—understanding market trends, emerging technologies, competitor moves, and evolving best practices to ensure the Lab’s backlog and POCs are forward‑looking, relevant, and strategically aligned. Role Overview : This role is the senior-most technical authority for the AI Innovation Lab, responsible for designing, building, and scaling enterprise-grade AI solutions with a focus on GenAI, agentic architectures, and intelligent automation. Leads multi-disciplinary engineering teams to deliver production-ready AI capabilities at startup speed, ensuring technical feasibility, scalability, and integration with enterprise systems. Requires deep hands-on expertise across GenAI, ML, architecture, and enterprise systems Must deliver working solutions in weeks, as an extension to research and prototypes Balances cutting-edge experimentation with production-grade rigor Designs for reuse and orchestration of digital workers/agents at scale Experience with LLMs, AI tools and techniques to experiment with use cases within the Innovation Lab with speed What You’ll Do AI Solution Architecture & Build Design and deliver end-to-end AI solutions, including: GenAI / LLM-based applications Agentic workflows and orchestration layers ML + analytics integration Define scalable architectures aligned to enterprise systems and data environments Rapid Prototyping & POC Delivery Lead engineering teams through rapid POC development cycles (weeks) Convert business problems into working AI solutions with measurable outputs Ensure solutions meet technical feasibility thresholds for scaling Platform & Reusability Strategy Build reusable: AI components Data pipelines Agent frameworks Enable cross-use-case reuse and enterprise scalability Engineering Leadership Lead distributed teams (onshore/offshore) across: AI/ML engineers Data engineers Full-stack developers Establish best practices across: MLOps / LLMOps DevOps Strong understanding of the importance of engineering resiliency, within the AI ecosystem. Responsible AI Integration & Production Readiness Ensure seamless integration with: Enterprise data platforms APIs, and legacy systems Identify risks, dependencies, and constraints early Prepare solutions for transition to execution factory / production environments Who You Are Bringing a Bachelor’s or Master’s degree - B.E. / B.Tech / M.S. / M.Tech / MCA degree in Computer Science, Technology, Engineering, Mathematics or a related subject area 12–18+ years in AI/ML, data engineering, and enterprise architecture Deep hands-on expertise in: GenAI / LLM frameworks Cloud platforms (AWS/Azure/GCP) API-based architecture and microservices Proven track record delivering AI solutions in production environments Skills That Will Help You Stand Out Combines research-level AI knowledge with enterprise delivery discipline Proven ability to deliver agent-based and GenAI solutions at scale Strong leadership of multi-POD, cross-functional engineering teams onshore and offshore Ability to translate ambiguous business problems into technical systems quickly Is able to negotiate senior business, technology and product management stakeholders, to socialize the POC outcomes, and ensure the final business needs are met.