Deutsche Bank
Financial Services
LeadEngineer
Neural analysis suggests this role is
optimal for Director candidates.
“Lead Engineer at Deutsche Bank. Skills: AI Delivery, Engineering Oversight, Agile Leadership, Stakeholder Management, AI Enablement. Build an AI platform. Build a scalable yet agile architecture”
What You'll Achieve.
Improve speed, quality, and predictability; Accountability for timelines, quality, cost, and risk; Focusing on outcomes over process; Improve engineering productivity; Improve quality; Improve operational efficiency
Industry & Context.
Evaluate trade-offs; Risk mitigation; Continuous improvement; Delivery insights
What They're Looking For.
Must Have
18+ years of experience in technology delivery and leadership, Significant time at Director or equivalent level, Deep working knowledge of AI/ML, Active experience in model performance optimization techniques, Active experience in eval frameworks, Active experience in GenAI applications, Active experience in governance considerations
Nice to Have
Engineering fluency rather than hands-on expertise, Ability to ask the right questions, Ability to evaluate trade-offs, Ability to guide teams toward sound technical decisions
What You'll Do.
Build a scalable yet agile architecture
Own end-to-end delivery
Drive predictable delivery
Anticipate delivery risks
Define and track delivery and engineering health metrics
Partner effectively with architects and senior engineers
Ensure adherence to engineering standards
Champion Agile principles
Align teams on planning
Drive continuous improvement
Lead multiple tribes deliveries
Act as the primary interface
Communicate delivery status
Build trust through transparency
Identify practical opportunities to use AI/GenAI
Ensure responsible AI adoption
Support teams in embedding AI-assisted tooling
Guide teams on pragmatic adoption of GenAI
Lead and develop engineering managers
Create a culture focused on execution excellence
How You'll Work.
Team & Collaboration
Cross-functional collaboration; Cross-functional programs; Across portfolios; Business, product, engineering, risk, and operations stakeholders; Data science, AI engineering, and platform teams
Communication Scope
Executive-ready manner; Cross-functional collaboration
Process & Methodology
Agile, Hybrid delivery models, Planning, Dependency management, Execution
Full Job Description
## _**Job Description:**_ **Job Title: Lead Engineer** **Corporate Title: Director** **Location: Bangalore, India** **Role Description** * We are seeking a delivery-focused Director with a strong understanding of the engineering and AI landscape, agile execution, and stakeholder management. This role is responsible for end-to-end delivery outcomes, ensuring teams operate effectively across modern technology stacks, while leveraging AI and automation to improve speed, quality, and predictability. * The role requires engineering fluency rather than hands-on expertise, the ability to ask the right questions, evaluate trade-offs, and guide teams toward sound technical decisions. The role will shape LLM performance, AI strategy for the company and AI platform development. **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 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** **AI Delivery & Execution Excellence ** * Build an AI platform that is foundational to the consumption of LLMs within the company * Build a scalable yet agile architecture that can adopt to changing AI landscape * Fine Tuning and Eval as integral part of execution cycle * Own end-to-end delivery of large, cross-functional programs with accountability for timelines, quality, cost, and risk. * Drive predictable delivery using Agile and hybrid delivery models, focusing on outcomes over process. * Anticipate delivery risks early and ensure timely mitigation. * Define and track delivery and engineering health metrics (flow, predictability, stability, and
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