Lead data and ai solution engineer

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