AI / ML Engineer

About The Role

Project Role: AI / ML Engineer

Project Role Description: Develops applications and systems that utilize AI tools, Cloud AI services, with a proper cloud or on-prem application pipeline with production-ready quality. Be able to apply GenAI models as part of the solution. Could also include, but not limited to, deep learning, neural networks, chatbots, and image processing.

Must-have skills: Machine Learning

Good-to-have skills: NA

Minimum 5 year(s) of experience is required.

Educational Qualification: 15 years of full-time education.

Summary

We are seeking a visionary AI Research and Innovation Sr. Principal to spearhead our efforts in Agentic AI—developing autonomous, goal-driven AI systems capable of reasoning, planning, and interacting in complex environments. This role is ideal for a thought leader passionate about pushing the boundaries of intelligent agents.

Roles & Responsibilities

• Lead R&D in agentic architectures, autonomous agents, including planning, memory, tool use, and self-reflection, human-agent collaboration, and model/agent drift detection.
• Design and prototype autonomous agents for real-world applications (e.g., enterprise automation, digital assistants, healthcare autonomous agents).
• Collaborate with solutioning, delivery, and engineering teams to integrate agentic capabilities into scalable systems across various industries. Collaborate with the Responsible AI team to ensure policies are baked into the solutions, with the consulting team to provide technical depth in AI, and with academia and industry partners for pushing research boundaries.
• Publish and present novel and innovative research findings in top AI venues.
• Develop a larger AI talent pool and foster a culture of continuous learning across the practice and organization. Mentor a team of researchers and engineers.
• Support client engagements by providing consulting and solutioning for complex client problems by bringing in niche AI skills and utilizing advanced internal and external frameworks and accelerators.

Professional & Technical Skills

• Deep expertise in reinforcement learning, autonomous agents, and multi-agent systems.
• Strong understanding of LLMs and their integration into agentic workflows.
• Experience with frameworks like LangChain, AutoGPT, or similar.
• Proven track record of innovation and publications.

Additional Information

The candidate should have a minimum of 15 years of experience in Machine Learning Operations.

Qualification

15 years of full-time education.