Data Science and AI Engineering Lead, VP
AI in this role
Job Description:
Job Title: Data Science and AI Engineering Lead, VP
Location: Pune, India
Role Description
Driving the creation of new AI solutions for Chief Strategy & Innovation Office(CSIO).
- We are seeking an AI Engineer with more than 18+ years of experience who will stand at the forefront of innovation, architecting, developing, and deploying groundbreaking AI solutions that redefine what's possible. We are seeking a visionary and highly motivated Engineer eager to leverage advanced AI models and platforms to conquer complex business challenges and accelerate digital transformation across Deutsche Bank.
- As Deutsche Bank enters a phase where a variety of data and AI development tools are becoming more accessible, we are seeking an experienced Data Scientist and AI Engineer to help drive the implementation and deliver our AI Strategy for the Deutsche Bank.
- The role holder will be expected to lead the design, development and implementation of new AI solutions for stakeholders across the Deutsche Bank. These solutions will vary in terms of complexity, but all will have the goal of simplifying and accelerating Operations and Controls activities, achieving cost save targets, and driving revenue growth.
What we’ll offer you
As part of our flexible scheme, here are just some of the benefits that you’ll enjoy:
- Best-in-class annual leave policy
- Gender-neutral parental leaves
- 100% reimbursement under childcare assistance benefit (gender-neutral)
- Sponsorship for industry-relevant certifications and education
- Employee Assistance Program for you and your family members
- Comprehensive hospitalization Insurance for you and your dependents
- Accident and term life Insurance
- Complementary health screening for 35 yrs. and above
Your key responsibilities
- Leadership (20%):
- Help lead and develop a high-performing Data Science and AI Engineering team
- Help drive the adoption of AI and analytics best practice across CSIO, IT (TDI), and Deutsche Bank more widely
- Foster a collaborative and innovative team environment, encouraging continuous learning and skill development on topics across AI
- 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
- Stakeholder Management and Governance (10%):
- Help ensure the CBIBOC Data Science and AI Engineering book of work is transparently documented and managed to ensure tasks are efficiently allocated and executed, and progress is easily tracked and reported
- Ensure AI governance requirements, as mandated by bank policy, regulation, or law, are adhered to for all new solutions developed
- Provide demos of new solutions, training materials, slides, and other materials as required to support the CBIBOC communication and upskilling agenda
- Hands-on Development of AI Solutions (70%):
- Lead by example, working with other Squad members to design, develop, and implement novel AI solutions
- Partner with business stakeholders and other Squad members to understand their needs and priorities, and identify new opportunities for the development or use of AI solutions
- Ensure new AI use cases (Squad projects) are rigorously evaluated and prioritized based on expected ROI, strategic alignment, technical feasibility and risk
- Ensure all new AI solutions are thoroughly tested, validated, controlled (e.g. implementation of guardrails, access permissions, etc.), and monitored on an ongoing basis
- Ensure all new AI solutions are recorded in a centralized inventory and brought through the required approval steps prior to production implementation
- Track against agreed KPIs to demonstrate the effectiveness and value of each AI solution (e.g. costs and benefits as well as accuracy/consistency/performance)
Your skills and experience
Strategic AI Solution Development:
- End-to-End AI Architecture & Leadership: Lead the design, architecture, and implementation of highly scalable and robust AI-powered applications and services utilizing Python, FastAPI/Flask, FastMcp LangGraph, ADK and Google VertexAI.
- Advanced Model Integration & Optimization: Architect, integrate, and expertly fine-tune large language models, with a strategic focus on the Gemini Model, for advanced tasks and cutting-edge generative AI applications.
- Demonstrable experience using Data Science / 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, Neo4J, etc.
- Experience with front-to-back AI solution design and architecture, particularly the design of agentic AI solutions
Scalable System Integration & Cloud Infrastructure
- API Architecture & Integration: Drive the design and implementation of seamless API architectures and integrations with diverse internal and external systems, ensuring optimal data flow and functionality across the enterprise.
- Cloud Infrastructure Leadership: Lead the deployment, management, and optimization of AI solutions on cloud platforms, leveraging services like GCP CloudRun/GKE, BigQuery, Cloud Composer, and CloudSQL for resilient data processing and infrastructure management.
Operational Excellence & Quality Assurance
- Code Quality & AIOps Governance: Establish and enforce rigorous code quality standards and best practices for software development and AIOps, ensuring clean, maintainable, and well-documented code across all AI projects.
- Advanced Testing & Deployment Oversight: Architect and execute comprehensive test strategies for AI solutions, leading the deployment and continuous monitoring of models in production environments, ensuring high performance and reliability.
- Thought Leadership & Cross-Functional Collaboration:
- Research & Innovation Leadership: Actively lead research into the latest advancements in AI, machine learning, and natural language processing, translating cutting-edge developments into innovative solutions and strategic initiatives.
- Cross-Functional Strategic Partnership: Collaborate closely with product managers, data scientists, and other engineering leaders to define strategy, align priorities, and ensure the successful delivery of high-quality, impactful AI products that meet business objectives.
- Demonstrable experience with data / feature engineering, data product creation, and modern data solutions such as BigQuery, Looker, PostgreSQL, Pinecone, Spark, MongoDB, Redis, Databricks, Denodo, Snowflake, etc.
- Strong knowledge of current best practice for AI risk management across the solution lifecycle, and how to leverage technology to implement these controls (e.g. from development, testing, and validation of new solutions to setting access controls/permissions, implementing guardrails, and automating performance monitoring and reporting / dashboards)
- Ability to write / review Python code and experience using AI coding assistants (Claude Code, Github Copilot, etc.). SQL and Java experience desirable but not essential.
- Experience developing production-grade software within a Software Development Lifecycle (SDLC) control framework
- The ability to balance people management, hands-on development work, and governance activities in a flexible day-to-day manner.
- The desire to grow and learn, keep up with the latest developments and new AI offerings emerging across the industry, and progress their Data Science / AI career.
Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.
How we’ll support you
- Training and development to help you excel in your career
- Coaching and support from experts in your team
- A culture of continuous learning to aid the progression of your career
- A range of flexible benefits that you can tailor to suit your needs
About us and our teams
Please visit our company website for further information:
https://www.db.com/company/company.html
We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.
Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.
We welcome applications from all people and promote a positive, fair and inclusive work environment.
How we rate this
Data Science and AI Engineering Lead, VP at Deutsche Bank rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Walk me through how you've used Claude in your day-to-day work.
- What are the limits of Gemini that you've run into, and how did you work around them?
- What's a project where you used Copilot hands-on?
- Walk me through how you've used LangChain in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: NLP, Claude, Gemini, Copilot, and LangChain. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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