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 an AI revolution.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on innovation and collaboration.
- Why this job: Shape the future of enterprise AI and make a real impact in finance.
- Qualifications: PhD or equivalent experience in Computer Science or related fields; strong ML engineering skills.
The predicted salary is between 120000 - 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.
- 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.
- 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 Executive Director — Production LLM Systems employer: TwinThread
At JP Morgan, we pride ourselves on being at the cutting edge of financial technology, offering a dynamic work environment that fosters innovation and collaboration. As a Generative AI Executive Director, you will not only lead transformative projects but also benefit from a culture that values diversity, inclusion, and continuous professional growth. Join us in a role where your expertise will directly impact our clients and the future of enterprise AI, all while enjoying the support of a global team dedicated to excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Generative AI Executive Director — Production LLM Systems
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Showcase your skills in action! Create a portfolio or GitHub repo with projects that highlight your expertise in LLM systems and AI. It’s a great way to impress potential employers.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to AI and ML. 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, you’ll be part of a community that values innovation and collaboration.
We think you need these skills to ace Generative AI Executive Director — Production LLM Systems
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Generative AI Executive Director role. Highlight your hands-on experience in ML engineering and any relevant projects that showcase your ability to deliver production-grade systems.
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. Be sure to mention specific achievements that demonstrate your technical leadership and innovative mindset.
Showcase Your Technical Skills:In your application, don’t shy away from diving into the technical details. We want to see your expertise in NLP, Computer Vision, and LLM algorithms. Mention any frameworks you've used, like Ray or DeepSpeed, to show us you’re ready to hit the ground running.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets the attention it deserves. Plus, it gives you a chance to explore more about our culture and values while you’re at it!
How to prepare for a job interview at TwinThread
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest advancements in NLP, Computer Vision, and LLM algorithms. Brush up on your hands-on experience with frameworks like Ray or DeepSpeed, as you’ll want to showcase your technical prowess during the interview.
✨Showcase Your Leadership Skills
As a Generative AI Executive 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 delivered impactful AI solutions in previous roles.
✨Communicate Complex Ideas Simply
You’ll be expected to explain intricate technical concepts to stakeholders at all levels. Practice breaking down complex ideas into digestible parts, so you can effectively communicate your vision and build trust with your audience.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you’ve faced in ML engineering and how you overcame them. Be ready to discuss your approach to architecting scalable systems and optimising performance.