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Job Description:
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Job Title Research AI Transformation Lead
Corporate Title Managing Director / Director
Location New York
Overview
Deutsche Bank Research is responsible for economic and financial analysis within Deutsche Bank Group and covers asset allocation and all major industry sectors. We analyze relevant trends for the bank in financial markets, the economy and society, highlight risks and opportunities and act as consultant for the bank, its clients and stake\-holders.
We are seeking an AI Transformation Lead to drive the strategic integration and adoption of AI technologies across the global division. This senior leadership role will shape the future of research analysis and digital content delivery by leveraging advanced AI capabilities.
The successful candidate will be responsible for defining and executing the AI strategy for the Research Division, identifying and prioritizing high\-impact use cases, and partnering with technology divisions to implement scalable solutions. This role requires a sophisticated understanding of both AI technologies and the complexities of financial analysis, coupled with executive\-level leadership, communication, and change management capabilities.
What We Offer You
- A diverse and inclusive environment that embraces change, innovation, and collaboration
- A hybrid working model, allowing for in\-office / work from home flexibility, generous vacation, personal and volunteer days
- Employee Resource Groups support an inclusive workplace for everyone and promote community engagement
- Competitive compensation packages including health and wellbeing benefits, retirement savings plans, parental leave, and family building benefits
- Educational resources, matching gift, and volunteer programs
What You’ll Do
- Set the AI strategy: Define and deliver a multi\-year AI roadmap for Research, aligned with business priorities and the bank’s broader digital agenda.
- Prioritize high\-value use cases: Partner with analysts to identify AI opportunities that improve workflows, strengthen research output, and generate measurable client and commercial impact.
- Lead delivery end to end: Oversee AI initiatives from concept and prototyping through production deployment, adoption tracking, and performance monitoring.
- Build scalable solutions: Work with Technology, data teams, vendors, and partners to design secure, robust, and production\-ready AI tools and platforms.
- Drive adoption and change: Champion AI across Research through stakeholder engagement, training, communication, and practical upskilling programmes.
- Ensure responsible AI governance: Establish controls for data privacy, model transparency, explainability, intellectual property, regulatory compliance, and ethical AI use.
Skills You’ll Need
- Educational qualifications: Advanced degree preferred in Computer Science, Artificial Intelligence, Data Science, Quantitative Finance or a related discipline.
- Senior AI transformation leadership: 10\+ years’ experience at the intersection of technology and financial services, with a track record of leading complex AI/ML initiatives from strategy to scaled delivery.
- AI strategy and execution: Proven ability to define AI roadmaps, build business cases, prioritize high\-impact use cases, and move initiatives from concept through production deployment.
- Technical fluency: Strong understanding of modern AI/ML techniques, including NLP, LLMs, generative AI, supervised and unsupervised learning, deep learning, cloud AI architectures and MLOps.
Skills That Will Help You Excel
- Research and markets expertise: Strong knowledge of capital markets, investment research methodologies, macroeconomic analysis, and quantitative and qualitative datasets across major asset classes.
- Executive stakeholder leadership: Ability to translate technical complexity into business strategy, influence senior stakeholders, lead cross\-functional teams, and operate effectively in a regulated global organization.
Expectations
It is the Bank’s expectation that employees hired into this role will work in the New York office in accordance with the Bank’s hybrid working model.
Deutsche Bank provides reasonable accommodations to candidates and employees with a substantiated need based on disability and/or religion.
The salary range for this position in New York, NY is 360k\-460k. Actual salaries may be based on a number of factors including, but not limited to, a candidate’s skill set, experience, education, work location and other qualifications. Posted salary ranges do not include incentive compensation or any other type of remuneration.
Deutsche Bank Benefits
At Deutsche Bank, we recognize that our benefit programs have a profound impact on our colleagues. That’s why we are focused on providing benefits and perks that enable our colleagues to live authentically and be their whole selves, at every stage of life. We provide access to physical, emotional, and financial wellness benefits that allow our colleagues to stay financially secure and strike balance between work and home. Click here to learn more!
Learn more about your life at Deutsche Bank through the eyes of our current employees: https://careers.db.com/life
The California Consumer Privacy Act outlines how companies can use personal information. If you are interested in receiving a copy of Deutsche Bank’s California Privacy Notice, please email [email protected] .
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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.
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or other characteristics protected by law. Click these links to view Deutsche Bank’s Equal Opportunity Policy Statement and the following notices: EEOC Know Your Rights ; Employee Rights and Responsibilities under the Family and Medical Leave Act ; and Employee Polygraph Protection Act .
Salary Context
This $360K-$460K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Deutsche Bank, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($410K) sits 91% above the category median. Disclosed range: $360K to $460K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Deutsche Bank AI Hiring
Deutsche Bank has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Columbus, NY, US. Compensation range: $460K - $460K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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