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Salary
≈ $143k – $267k per year (Estimated)
Location
In office (London)
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Jan 15, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

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.

Required Qualifications, Capabilities, and Skills:

  • 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, Capabilities, and Skills:

  • 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.

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