Generative AI Director

Generative AI Director

Full-Time 100000 - 150000 £ / year (est.) No working from home possible
TwinThread

At a Glance

  • Tasks: Lead the design and delivery of cutting-edge AI systems that transform financial technology.
  • Company: Join JP Morgan's Chief Analytics Office and be part of a tech-driven culture.
  • Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
  • Other info: Be part of a diverse team driving innovation in a fast-paced environment.
  • Why this job: Shape the future of enterprise AI and make a real impact in finance.
  • Qualifications: PhD or equivalent experience in a quantitative field and extensive ML engineering skills.

The predicted salary is between 100000 - 150000 £ per year.

Step into a pivotal role at the forefront of JP Morgan’s AI transformation. As part of the Chief Analytics Office (CAO), you’ll drive innovation and shape the future of financial technology. You’ll collaborate with talented teams, architect impactful solutions, and see your work deliver measurable results across the firm. This is your opportunity to influence strategy, build production-grade systems, and unlock new possibilities for our clients and stakeholders. Join us and help define the next era of enterprise AI.

As a Generative AI Executive Director in the Chief Analytics Office, you will lead the design and delivery of production‑grade LLM systems that power mission‑critical products for thousands of professionals. Your technical leadership will empower teams to innovate and accelerate the adoption of AI at scale.

Job Responsibilities
  • You will architect scalable APIs and agentic workflows, enabling automation and efficiency across the firm.
  • Architect and deliver production LLM‑based systems for text, image, speech, and video applications.
  • Own end‑to‑end delivery, performance, and continuous improvement of LLM Suite products.
  • Working closely with ML Engineering, Product Management, and Cloud Engineering, you will ensure our AI solutions are reliable, secure, and built for real business impact.
  • Bridge advanced AI research with robust engineering to build innovative, production‑ready solutions.
  • Drive results with an entrepreneurial mindset in a fast‑paced, high‑impact environment.
Required Qualifications, Capabilities, and Skills
  • Hold a PhD or possess equivalent experience in Computer Science, Mathematics, Statistics, or a related quantitative discipline.
  • Demonstrate extensive hands‑on experience in ML engineering, with a proven track record of shipping production AI systems.
  • Bring deep expertise in NLP, Computer Vision, and/or Multimodal LLM algorithms, with a strong foundation in statistics, optimization, and ML theory.
  • Apply practical experience implementing distributed, multi‑threaded, and scalable applications using frameworks such as Ray, Horovod, or DeepSpeed.
  • Communicate complex technical concepts effectively and build trust with stakeholders at all levels.
Preferred Qualifications, Capabilities, and Skills
  • Design and deploy production ML pipelines using DAG frameworks, including custom operator development and pipeline optimization.
  • Architect and implement high‑throughput, low‑latency microservices with gRPC, REST, and GraphQL, including protocol buffer schema design, streaming endpoints, and load balancing.
  • Apply hands‑on experience with parameter‑efficient fine‑tuning (LoRA, QLoRA, IA3), model quantization (INT8, FP16, GPTQ), and quantization‑aware training for LLMs at scale.
  • Demonstrate deep knowledge of distributed training strategies, memory optimization, and inference acceleration for large‑scale multimodal models.
  • Orchestrate advanced agentic workflows, including multi‑agent coordination, stateful task management, and integration with enterprise event‑driven architectures.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.

Generative AI Director employer: TwinThread

At JP Morgan, we pride ourselves on being at the cutting edge of financial technology, offering a dynamic work environment where innovation thrives. As a Generative AI Director, you will not only lead transformative projects but also benefit from a culture that values collaboration, diversity, and continuous learning. With access to top-tier resources and a commitment to employee growth, this role provides a unique opportunity to make a significant impact in a fast-paced, high-stakes industry.

TwinThread

Contact Details:

TwinThread Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Generative AI Director

Tip Number 1

Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.

Tip Number 2

Show off your skills! Create a portfolio or a GitHub repository showcasing your projects, especially those related to AI and ML. This gives potential employers a taste of what you can do.

Tip Number 3

Prepare for interviews by practising common questions and scenarios specific to generative AI. We recommend doing mock interviews with friends or using online platforms to boost your confidence.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!

We think you need these skills to ace Generative AI Director

Machine Learning Engineering
Natural Language Processing (NLP)
Computer Vision
Multimodal LLM Algorithms
Statistics
Optimization
Distributed Applications

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Generative AI Director role. Highlight your hands-on experience in ML engineering and any relevant projects that showcase your expertise in NLP and multimodal LLM algorithms.

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about AI and how your background makes you the perfect fit for this role. Don’t forget to mention specific achievements that demonstrate your ability to drive innovation.

Showcase Your Technical Skills:In your application, be sure to detail your technical skills, especially those related to architecting scalable APIs and production ML pipelines. We want to see your experience with frameworks like Ray or DeepSpeed, so don’t hold back!

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at JP Morgan!

How to prepare for a job interview at TwinThread

Know Your Stuff

Make sure you brush up on your knowledge of generative AI, especially in areas like NLP and computer vision. Be ready to discuss your hands-on experience with production AI systems and how you've tackled challenges in ML engineering.

Showcase Your Leadership Skills

As a Generative AI Director, you'll need to demonstrate your ability to lead teams and drive innovation. Prepare examples of how you've successfully managed projects, collaborated with cross-functional teams, and influenced strategy in previous roles.

Communicate Clearly

You’ll be expected to explain complex technical concepts to stakeholders at all levels. Practice articulating your ideas clearly and concisely, focusing on how your work can deliver measurable results for the firm.

Prepare for Technical Questions

Expect in-depth technical questions about scalable APIs, microservices, and distributed training strategies. Review relevant frameworks and be ready to discuss your approach to building production-grade systems that are reliable and efficient.