Gen AI Engineering Leader

About the Role

The Generative AI (GenAI) Engineering Leader will lead the organizations AI-driven product engineering and innovation strategy. This role requires a senior technology leader (14+ years) with extensive experience in product development, product engineering, and architecture leadership.

The individual will be responsible for building Solutions, define and operationalize the GenAI roadmap, embed AI-infused engineering practices, and drive capability development programs across global teams. The person needs to be hand-on with a capability to develop and build things as individual Contributor. This position demands deep expertise in AWS, AI/ML, and full-stack engineering, along with strong business acumen and the ability to translate AI potential into tangible outcomes. The ideal candidate embodies a product and learning mindset, fostering innovation, scalability, and measurable impact across enterprise products and platforms.

Responsibilities

AI-Infused Engineering

• Lead creation of Multiple AI-driven Solutions, Client Solution, PoV, PoC, reusable prompt libraries, Best Practices and automation frameworks for engineering and delivery functions.
• Architect and oversee multi-agent Agentic AI systems leveraging AI Frameworks like LangChain, LlamaIndex, Langsmith, AIOps, RAG, model orchestration frameworks like AWS Bedrock, Vertex AI, Crew.ai, etc. and ensuring fairness, compliance, and security in all deployments.
• Work with leadership to further refine Generative AI and ML capabilities within SDLC processesautomating code generation, documentation, testing, and architecture synthesis.
• Drive the use of AI observability tools, performance tuning, and token optimization to ensure efficiency and cost control.
• Serve as the organizations AI thought leader, presenting innovations to clients, partners, and executive forums.

Talent Development and Capability Building

• Building community of senior tech talent: Identify talent (internal and external) and nurture a community or practice for AI architects and technical leads.
• Strengthen engineering bench talent: Ensure a strong engineering bench to support business growth. Implement upskilling and cross-skilling programs tailored for both new graduates and experienced associates.
• Foster collaboration: Promote cross-functional collaboration, drive innovation, and facilitate the sharing of best practices across various verticals and client projects.
• Consulting and Technical Guidance: Mentor senior engineers and architects, nurturing next-generation AI leaders and provide expert technological and architectural consulting to address complex digital challenges.
• Work with leadership to further scaling GenAI Center of Excellence (CoE) practices and knowledge across the enterprise.
• Strengthen AI Training Programs - Collaborate with HR and L&D teams Design, Refine and execute structured learning pathways and certification programs for engineers, data scientists, and product teams.

Generative AI and ML Expertise

• Proficiency with AI development frameworks: LangChain, Hugging Face, OpenAI APIs, PyTorch, and TensorFlow.
• Proven experience in GenAI Solutioning, LLMs, prompt engineering, fine-tuning, model optimization, and evaluation.
• Hands-on experience in RAG pipelines, vector databases, and embedding strategies, Agentic Architecture, Self healing systems, AI Guardrailing.
• Understanding of AI governance, bias detection, explainability, and model lifecycle management.
• Knowledge of AI cost optimization and usage analytics across model providers.

Product and Platform Engineering

• 12+ years in product development and engineering, preferably within large-scale or SaaS environments.
• Expertise in defining technology roadmaps, engineering standards, and reference architectures.
• Deep proficiency in scalable architecture design for MACH architecture, and full-stack technologies (Java, Python, Node.js, React, etc.).
• Experience across DevOps/MLOps/AIOps, CI/CD, cloud automation, and containerization (Docker, Kubernetes).
• Skilled in application performance optimization and proficient in databases (SQL, NoSQL, graph, and vector stores) and data modelling for AI applications.
• Strong grounding in infrastructure-as-code (Terraform, CloudFormation) and cloud security principles.

Cloud and Infrastructure Mastery

• Deep knowledge of AWS services (SageMaker, Bedrock, ECS, Lambda, Redshift, IAM, KMS).
• Experience designing multi-cloud and hybrid architectures across AWS, Azure, and GCP.

Architecture and Governance Leadership

• Define and enforce AI and product architecture standards, ensuring modularity, scalability, and compliance.
• Evaluate and onboard AI tools, models, and providers based on ROI, compliance, and ecosystem fit.
• Establish reference implementations and accelerators to enable rapid GenAI adoption.
• Certification: AWS/Azure/GCP Certified Solution Architect Professional.
• Generative AI or Applied AI Certification (Google/AWS/Microsoft).
• TOGAF / SAFe / SCRUM desirable for architecture governance.

Qualifications

Minimum 12 years of professional experience in product development, digital platforms, or enterprise architecture and GenAI. Proven leadership of cross-functional global teams across engineering, AI, and DevOps. Background in engineering process excellence, Agile transformation, and innovation frameworks. Exposure to Architecting and delivering Software product, multi-region rollouts solutions.

Required Skills

Deep expertise in AWS, AI/ML, and full-stack engineering, along with strong business acumen and the ability to translate AI potential into tangible outcomes.

Preferred Skills

The ideal candidate embodies a product and learning mindset, fostering innovation, scalability, and measurable impact across enterprise products and platforms.