About client:

Global AI & Innovation team to build next-generation AI platforms, autonomous agents, and real-time intelligence solutions that transform how a global enterprise operates and serves its customers.

Position Summary:

The company is seeking a highly experienced, hands-on Senior Manager, AI Engineering & Delivery to lead the Hyderabad GCC AI delivery organization and serve as a critical execution partner to the Global AI & Innovation leadership team.

This role will own the design, delivery, operationalization, and support of enterprise AI, machine learning, Generative AI, and Agentic AI solutions across the prioritized global pipeline.

The successful candidate will manage a multidisciplinary team of AI/ML Engineers, Agent Developers, Data Scientists, MLOps resources, contractors, and delivery partners.

Key Responsibilities:

- Lead end-to-end delivery of AI, ML, Generative AI, and Agentic AI initiatives across the prioritized global portfolio.

- Own solution architecture and technical design for AI/ML applications, AI microservices, RAG solutions, and multi-agent workflows.

- Build, lead, coach, and develop a high-performing multidisciplinary GCC team.

- Serve as the primary GCC AI point of contact for the onshore team and business stakeholders.

- Operationalize AI governance requirements, including security-by-design and Responsible AI safeguards.

- Own and drive continuous AI learning, enablement, and Responsible AI awareness.

- Serve as the first-level escalation point for delivery, production, model, and agent issues.

- Report directly to the Global Head, AI & Innovation to translate strategy into an executable roadmap.

Required Qualifications:

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related discipline.

- 12+ years of progressive experience across software engineering, data science, AI/ML engineering, or digital solution delivery.

- 5+ years leading multidisciplinary AI/ML or advanced engineering teams.

- Demonstrated success designing, deploying, and supporting production-grade enterprise AI/ML or Generative AI solutions.

Technical Skills:

- AI/GenAI: LLMs, prompt engineering, AI agents, multi-agent orchestration, RAG, Semantic Kernel, LangChain.

- Data Science: Statistics, predictive modeling, NLP, neural networks, optimization techniques.

- Engineering: Python, SQL, REST services, Docker, Kubernetes, CI/CD, Azure/AWS.

- Data Engineering: Snowflake, Azure Data Factory, Spark, Kafka, Vector databases.

Leadership Competencies:

- Enterprise thinking with disciplined execution.

- Strong ownership, urgency, and accountability.

- Ability to influence without direct authority.

- Talent development and inclusive team leadership.