Data Science and AI Engineering Lead​, VP

Overview

Lead the creation, architecture, development and deployment of new AI solutions for Deutsche Bank’s Chief Strategy & Innovation Office (CSIO). The role combines Data Science and AI Engineering leadership, hands-on solution development, stakeholder management and AI governance.

What you'll do

• Help lead and develop a high-performing Data Science and AI Engineering team.
• Drive adoption of AI and analytics best practices across CSIO, IT (TDI), and Deutsche Bank more widely.
• Foster a collaborative and innovative team environment, encouraging continuous learning across AI topics.
• Stay abreast of industry trends and emerging technologies in data warehousing, business intelligence, and cloud analytics, particularly within the Google Cloud Platform ecosystem.
• Conduct performance reviews, provide constructive feedback, and support career progression for team members as needed.
• Help ensure the CBIBOC Data Science and AI Engineering book of work is transparently documented and managed so tasks are efficiently allocated and executed and progress is tracked and reported.
• Ensure AI governance requirements mandated by bank policy, regulation, or law are followed for all new solutions.
• Provide demos of new solutions, training materials, slides, and other materials supporting the CBIBOC communication and upskilling agenda.
• Design, develop, and implement novel AI solutions with other Squad members.
• Partner with business stakeholders and Squad members to understand needs and priorities and identify opportunities for developing or using AI solutions.
• Evaluate and prioritize new AI use cases based on expected ROI, strategic alignment, technical feasibility and risk.
• Test, validate, control and continuously monitor new AI solutions, including guardrails and access permissions.
• Record new AI solutions in a centralized inventory and complete required approval steps before production implementation.
• Track agreed KPIs to demonstrate each AI solution’s effectiveness and value, including costs, benefits, accuracy, consistency and performance.
• Lead the design, architecture, implementation and deployment of scalable AI-powered applications and services.
• Design and implement API architectures and integrations with internal and external systems.
• Lead deployment, management and optimization of AI solutions on cloud platforms.
• Establish and enforce code quality standards and AIOps best practices.
• Architect and execute comprehensive AI solution test strategies and lead production deployment and continuous model monitoring.
• Lead research into advances in AI, machine learning and natural language processing and translate them into innovative solutions and strategic initiatives.
• Collaborate with product managers, data scientists and engineering leaders to define strategy, align priorities and deliver AI products.
• Balance people management, hands-on development and governance activities.
• Leverage AI tools to enhance productivity and optimize workflows while applying critical judgment for responsible and ethical use of data and AI outputs.

What you'll need

• More than 18+ years of experience.
• Experience designing, architecting and implementing highly scalable and robust AI-powered applications and services using Python, FastAPI/Flask, FastMcp, LangGraph, ADK and Google VertexAI.
• Experience architecting, integrating and fine-tuning large language models, with a strategic focus on the Gemini Model, for advanced tasks and generative AI applications.
• Demonstrable experience using Data Science and AI developer tools and platforms such as Github, VS Code, PyTorch, TensorFlow, scikit-learn, MLflow, Weights and Biases, Jupyter Notebook, Hugging Face, Langchain, Langgraph, Google Vertex and Neo4J.
• Experience with front-to-back AI solution design and architecture, particularly agentic AI solutions.
• Experience designing and implementing API architectures and integrations with diverse internal and external systems.
• Experience deploying, managing and optimizing AI solutions on cloud platforms using services such as GCP CloudRun/GKE, BigQuery, Cloud Composer and CloudSQL.
• Experience establishing code quality standards and best practices for software development and AIOps.
• Experience architecting and executing comprehensive test strategies for AI solutions and leading production model deployment and monitoring.
• Experience researching AI, machine learning and natural language processing advancements and translating them into solutions and strategic initiatives.
• Experience collaborating with product managers, data scientists and engineering leaders to define strategy, align priorities and deliver AI products.
• Demonstrable experience with data and feature engineering, data product creation, and modern data solutions such as BigQuery, Looker, PostgreSQL, Pinecone, Spark, MongoDB, Redis, Databricks, Denodo and Snowflake.
• Strong knowledge of current best practice for AI risk management across the solution lifecycle and how to implement controls using technology.
• Ability to write and review Python code and experience using AI coding assistants such as Claude Code and Github Copilot.
• Experience developing production-grade software within a Software Development Lifecycle (SDLC) control framework.
• Ability to balance people management, hands-on development work and governance activities.
• Desire to grow and learn, keep up with latest developments and new AI offerings, and progress a Data Science and AI career.
• Proven ability to leverage AI tools to enhance productivity and optimize workflows while applying critical judgment for responsible and ethical use of data and AI outputs.

Nice to have

• SQL and Java experience.

Details

• Location: Pune, India.