To lead and optimize GenAI & Agentic AI Operations by driving efficient deployments, automation, and governance across platforms. The role ensures seamless issue resolution, performance monitoring, cost optimization and stakeholder coordination to enable scalable, compliant, cost-effective and high-performing GenAI & Agentic AI services.
- Lead deployments for GenAI pipelines and Agentic AI pipelines in various Data & AI platforms
- Lead optimization and streamlining of GenAI & Agentic AI Ops processes and resource allocation
- Lead GenAI & Agentic AI Ops issue/incident tracking and reporting, coordinate concerted issue/incident resolution with related parties
- Develop automation scripts and methods to reduce manual effort in GenAI & Agentic AI deployments
- Develop data collection and analytics methods for mining and reporting of GenAI & Agentic AI Ops performance metrics and insights
- Explore and implement new GenAI & Agentic AI Ops capabilities and tools to increase automation coverage and deployment velocity
- Design and implement workflows and controls to strengthen governance and compliance for GenAI & Agentic AI Ops
- Drive Operations Excellence projects and initiatives to continually improve GenAI & Agentic AI Ops capabilities and key metrics
- Coordinate with GenAI & Agentic AI Ops stakeholders to ensure seamless operations and communications
- Bachelor's degree in AI, Data Science, Computer Science, Engineering, or a related field (Master's degree preferred)
- 5+ years of experience in Data & AI Engineering or Operations, with a focus on deploying and managing data engineering and machine learning pipelines
- Hands-on exposure to operationalization of GenAI and Agentic AI implementation
- Broad expertise across Data & AI pillars, including AI/ML, Data Engineering, and Analytics
- Proficiency in programming languages such as Python, Java, Scala, or R, and strong command of SQL and Big Data querying tools
- Hands-on experience with GenAI/Agentic AI frameworks and libraries (e.g., LangChain, LangGraph, agentcore, MCP)
- Familiarity with machine learning/AI frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn)
- Familiarity and relevant certifications on cloud platforms (AWS, GCP, or Azure) is a plus
- Strong understanding of SDLC, DevOps best practices, and Agile methodologies
- Proven ability to design and implement automation for deployment and monitoring of GenAI and Agentic AI workflows
- Experience in developing operational dashboards and performance analytics for Data & AI platforms
- Prior experience in financial services or insurance industry is highly advantageous
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders
- Strong problem-solving skills, a proactive mindset, and a continuous improvement orientation
- High level of integrity, accountability, and a collaborative team spirit
- Fast in learning new technology, open mindset and adaptable to changes, and takes initiative to drive operational excellence
