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Lead Engineers and Developers: Design and execute our comprehensive Gen AI and Metrics strategy aligned with the organization's overall goals and help identify opportunities to automate and optimize business processes using generative AI
Lead and develop a High Performing Team: Lead, mentor, and manage a team of ML Engineers, Data Engineers and AI practitioners, ensuring retention and growth of top talent in this space
Drive Innovation: Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to develop impactful solutions and foster a culture of innovation and experimentation within the team
Hands-On Execution and Delivery: Oversee the end-to-end development and deployment of Solutions, ensuring timely delivery and adherence to quality standards. Actively involved in design and coding
Collaboration and Stakeholder Interaction: Build strong relationships with key stakeholders, including executives, business leaders, and clients. Collaborate with technical teams to ensure the feasibility and scalability of AI solutions to solve business problems
Deep understanding of latest and upcoming AI trends: Stay up to date with the latest advancements in the field and identify emerging opportunities. Lead and participate in research activities to explore and advance state-of-the-art generative AI techniques. Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field
Regulatory and Ethical Compliance: Ensure that AI initiatives meet regulatory, data privacy, ethical AI standards, and corporate governance policies requirements while pushing the boundaries of technology innovation
Requirements
10+ years of experience in AI, ML and Data Engineering and development
5+ years of leadership experience managing distributed teams
Deep technical expertise in middleware technologies and their application in AI systems
Strong understanding of modern software development methodologies (Agile, DevOps)
Experience with Kafka and modern data stack like Trino, Iceberg, Databricks etc.
Proficient in Python and key python libraries, Agentic Frameworks, MCP
Expertise in containerization (Docker), orchestration (Kubernetes), and experience with CI/CD pipelines for AL/ML model deployment
Knowledge of distributed training and parallel processing frameworks is also required to handle large-scale AI projects efficiently
Experience with AWS services and infrastructure related to AI/ML, workflow
Experience in pattern recognition and predictive modeling
Solid understanding of experimental design, hypothesis testing, and casual inference methods
Strong analytical and problem-solving skills
Strong problem-solving and critical-thinking abilities, with a demonstrated ability to tackle open-ended problems and drive projects to completion
Financial industry experience would be a plus
Bachelor’s/Master’s degree or equivalent in Computer Science, Data Science, Statistics, or a related field