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For Companies At a Glance
- Tasks: Design and deploy innovative AI agents that transform business operations.
- Company: Join J.P. Morgan, a global leader in financial services.
- Benefits: Competitive salary, professional growth, and a collaborative work environment.
- Why this job: Make a real impact on the future of finance with cutting-edge AI technology.
- Qualifications: Advanced degree in relevant fields and experience in AI applications.
- Other info: Diverse and inclusive culture with strong support for career development.
The predicted salary is between 48000 - 72000 £ per year.
Join us to shape the future of AI-driven business operations. You will have the opportunity to create scalable, safe, and reliable agentic solutions that transform how we work. We value your expertise in building multi-agent systems and your passion for collaborating across teams. At our company, you can grow your career, expand your skills, and make a meaningful impact. Be part of a team that thrives on innovation and continuous improvement.
As an AI Engineer in our Agentic AI Solutions team, you will design, build, and deploy autonomous and assistive AI agents that streamline complex workflows. You will collaborate with cross-functional partners to translate operational needs into robust multi-agent systems, leveraging advanced frameworks and technologies. Your work will directly impact our business by delivering scalable and reliable AI solutions. We foster a culture of innovation, learning, and teamwork, where your contributions are valued and your growth is supported.
Responsibilities
- Architect, develop, and productionize autonomous and assistive AI agents to enhance operations.
- Design multi-agent systems, including role definition, tool integration, planning, memory, and workflow orchestration using modern agent frameworks.
- Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search with vector databases, including indexing, retrieval policies, and evaluation.
- Build and integrate agent tools and APIs to connect agents with external services, databases, and internal systems, ensuring robust output parsing and error handling.
- Practice advanced prompt engineering and implement output validation and guardrails to reduce hallucinations.
- Design microservices-based architectures and orchestrate multi-step workflows; instrument agents for tracing, metrics, and feedback loops.
- Partner with stakeholders to define requirements, design intuitive human-AI interfaces, and deliver measurable business impact.
- Analyze data to inform agent capabilities, optimize retrieval, and drive data-driven decision-making; conduct A/B tests and performance evaluations.
- Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices.
Qualifications
- Advanced degree in Computer Science, Data Science, Machine Learning, or related field.
- Experience building and deploying agentic AI applications in production environments.
- Expertise with ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
- Proficiency in Python; experience writing comprehensive tests and building evaluation harnesses for agents and prompts.
- Hands-on experience with agent frameworks such as LangChain, CrewAI, AutoGen, LangGraph.
- Knowledge of generative models including transformers, GANs, VAEs, and diffusion models.
- Understanding of data preprocessing, feature engineering, and model/agent evaluation techniques.
- Familiarity with cloud platforms and containerization technologies.
- Strong problem-solving skills and ability to work independently and collaboratively.
- Effective communication skills for technical and non-technical audiences.
Preferred Qualifications
- Experience in financial services, especially investment banking operations.
- Experience fine-tuning small language models with approaches like LoRA, QLoRA, DoRA; quantization and distillation.
- Familiarity with prompt optimization frameworks and building prompt pipelines and evaluation suites.
- Experience with distributed computing, data sharding, and performance optimization.
- Hands-on experience with AWS services related to AI deployment and workflow orchestration.
Why Join Us?
We offer a competitive salary and benefits package, opportunities for professional growth, and a collaborative, innovative environment focused on responsible AI. You will work on impactful projects that shape the future of finance and have the chance to make a real difference.
Applied AI Lead Engineer - Agentic Systems in London employer: JPMorganChase
Contact Detail:
JPMorganChase Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI Lead Engineer - Agentic Systems in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and multi-agent systems. This will give you an edge and demonstrate your hands-on experience when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to AI engineering. Practice explaining your thought process clearly, as communication is key in collaborative environments.
✨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, it shows you’re genuinely interested in joining our innovative team.
We think you need these skills to ace Applied AI Lead Engineer - Agentic Systems in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with multi-agent systems and AI frameworks in your application. We want to see how your skills align with the role, so don’t hold back on showcasing your expertise!
Tailor Your Application: Take a moment to customise your CV and cover letter for this specific role. Mention how your background in AI aligns with our mission to innovate and improve business operations. It’ll make your application stand out!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see why you’re the perfect fit!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at JPMorganChase
✨Know Your Tech Inside Out
Make sure you’re well-versed in the ML frameworks mentioned in the job description, like PyTorch and TensorFlow. Brush up on your Python skills and be ready to discuss how you've implemented agent frameworks like LangChain or CrewAI in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in AI development. Think about times when you had to optimise workflows or enhance agent capabilities, and be ready to explain your thought process clearly.
✨Collaborate and Communicate
Since this role involves working with cross-functional teams, practice articulating your ideas to both technical and non-technical audiences. Be prepared to discuss how you’ve successfully partnered with stakeholders in previous roles to deliver impactful AI solutions.
✨Ask Insightful Questions
At the end of the interview, don’t shy away from asking questions that show your interest in the company’s AI initiatives. Inquire about their approach to innovation and how they measure the success of their AI projects. This demonstrates your enthusiasm and strategic thinking.
