Lead Generative AI Engineer - Python and LangChain

This is a role responsible for architecting, designing, and leading the development of innovative and scalable solutions for Retail Bank business with a close focus on generative AI capability based solutions. The overall objective is to leverage technical expertise and skills to drive the execution of key AI initiatives.

Responsibilities:

• Lead analytics to deepen core areas for Retail Bank business through different analytical solutions with a focus on leveraging Generative AI capabilities to enhance productivity and build highly customized solutions.
• Architect, design, and lead the development of production-grade Generative AI applications and complex Agentic solutions.
• Evaluate different agentic architectures and evolving industry practices to select the optimal approach for business problems.
• Design and implement agent training, performance measurement, correction, and feedback processes, and create/articulate new architectural options.
• Ensure solutions meet stringent compliance, security, and performance management standards.
• Collaborate with and advise business stakeholders on the scope and capabilities of Generative AI solutions.
• Mentor other data scientists in the team, training them in advanced Agentic solution development and software engineering best practices.

Qualifications:

• 4-7 years of overall experience with preferred experience in architecting and developing production-ready Gen AI RAG or Agent-based solutions.
• Mastery of Python, AI/ML frameworks (PyTorch, TensorFlow, LangChain), MLOps, and cloud-native architectures (Kubernetes).
• Expert-level understanding of Agentic solution design, including architecture selection, memory management, hallucination control, and reinforcement learning feedback loops.
• Strong experience in architecting and designing highly scalable, available, and performant technology solutions.
• Deep expertise in Agent training, performance measurement, and feedback processes.
• In-depth knowledge of compliance, security, and performance management in a production environment.

Education:

• Bachelor's/University degree and relevant experience; Master's degree preferred in Computer Science, AI, Engineering, or a related quantitative field.

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