Gen AI Lead

Define governance frameworks to establish standards for Gen AI product development, including ethical and responsible AI practices. Deliver service readiness by ensuring Gen AI solutions meet Service Acceptance Criteria for successful deployment. Ensure compliance and data security by aligning development with regulatory, security, and industry requirements throughout the lifecycle. Oversee DevOps, DataOps, and MLOps to ensure Gen AI solutions adhere to coding, security, and performance standards. Promote FAIR data principles by championing findability, accessibility, interoperability, and reusability in data pipelines and Gen AI solutions.
10 plus years of experience in software engineering, data engineering, and cloud engineering, with recent leadership in Gen AI and ML solution delivery. Deep technical mastery in data engineering, software engineering, and cloud platforms, combined with advanced knowledge of Generative AI systems and frameworks. Expertise in AI engineering principles, including MLOps, prompt engineering, model deployment, and operationalizing large language models (LLMs). Strong knowledge and practical application of DevOps, MLOps, and DataOps methods, processes, and tooling. Demonstrated product development and product management experience, with emphasis on Gen AI features and capabilities. Ability to provide technical thought leadership in Generative AI and Data & Analytics. Exceptional stakeholder management, communication, and collaboration abilities in complex environments. Proven problem-solving, analytical thinking, and a collaborative, team oriented mindset. Hands-on experience delivering Gen AI solutions from ideation through productization, driving technical innovation and transformation. Familiarity with Data Mesh and Data Product concepts for modern data architecture. Proficient in Agile methodologies, iterative development, and delivering value in cross functional teams. Demonstrated capability in designing, implementing, and optimizing data pipelines and ETL processes using state-of-the-art tools. Skilled at architecting and managing secure, scalable AWS environments and working experience in the data & analytics services such as Amazon EC2, AWS Lambda, AWS Fargate, Amazon ECS, Amazon EKS, Amazon S3, AWS Glue, Amazon RDS, Amazon DynamoDB, Amazon Aurora, Amazon SageMaker, Amazon Bedrock (including LLM hosting and management). Expertise in workflow orchestration tools such as Apache Airflow. Experience implementing DataOps best practices and tooling, including DataOps.Live. Advanced skills in data storage and management platforms like Snowflake. Ability to deliver insightful analytics via business intelligence tools such as Power BI. Full-stack development experience: backend (Node.js, Python), frontend (ReactJS). Demonstrated experience designing and implementing Generative AI solutions (chatbots, digital assistants, content generation, etc.). Hands on implementation and operation of AI/ML models with services like Amazon SageMaker. Advanced proficiency in Python and related AI/ML productivity libraries. Expertise in SQL and NoSQL database technologies.