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- Tasks: Design and develop cutting-edge AI agents that transform business operations.
- Company: Join a forward-thinking company focused on innovative AI solutions.
- Benefits: Competitive salary, professional growth opportunities, and a collaborative work culture.
- Why this job: Make a real impact in the future of AI-driven finance.
- Qualifications: Advanced degree in relevant fields and experience with AI applications.
- Other info: Dynamic environment with a focus on responsible AI and continuous improvement.
The predicted salary is between 36000 - 60000 £ 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.
Job 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.
- 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.
- 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.
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 employer: Jpmorgan Chase & Co.
Contact Detail:
Jpmorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI Lead Engineer - Agentic Systems
✨Tip Number 1
Network like a pro! Reach out to people 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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and multi-agent systems. This gives you a chance to demonstrate your expertise and passion, making you stand out to employers.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to AI solutions. Practice explaining your thought process clearly, as communication is key when collaborating across teams.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in being part of our innovative team.
We think you need these skills to ace Applied AI Lead Engineer - Agentic Systems
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with multi-agent systems and AI applications. We want to see how your skills align with our mission to innovate and improve business operations.
Showcase Your Passion: Let us know why you're excited about the role! Share your enthusiasm for AI and how you envision contributing to our team. A genuine passion can really make your application stand out.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to describe your experiences and achievements. We appreciate a well-structured application that gets straight to the point!
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 Jpmorgan Chase & Co.
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like PyTorch, TensorFlow, and the various agent frameworks. Brush up on your Python skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in AI or multi-agent systems. Think about challenges you've faced and how you approached them, as this will demonstrate your critical thinking and adaptability.
✨Collaborate and Communicate
Since the role involves working with cross-functional teams, be ready to discuss your experience collaborating with others. Highlight any instances where your communication skills helped bridge gaps between technical and non-technical stakeholders.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s approach to AI and their future projects. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values, especially around innovation and teamwork.
