Senior Lead Software and Data Engineer - Agentic Commerce

JPMorganChase; Greater London; On-site; GBP 140,000 - 180,000; Full time

Job summary

J.P. Morgan in London seeks a Senior Lead Software Engineer to steer architecture for B2B agentic commerce, ML model training and governance, and secure, scalable systems.

You will set technical direction, shape agent interactions, and drive enterprise AI practices while collaborating with risk, product, and platform teams. Strong Python/Java, Kubernetes, and ML experience required.

Qualifications

• Formal training or certification on software engineering concepts.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Advanced in one or more programming languages, with strong Python and/or Java experience.
• Proven experience shipping production LLM agents or multi-agent systems.
• Proven experience designing end-to-end ML platforms or MLOps pipelines.
• Experience designing secure distributed systems, including identity, authorization, and service-to-service trust.
• Strong understanding of CI/CD, Application Resiliency, and Security in an Agile environment.
• Knowledge of the financial services industry IT systems is a plus.

Responsibilities

• Sets the technical direction and reference architecture for B2B agentic commerce and A2A communication.
• Designs information barriers and authorization for agents acting for different counterparties.
• Defines the MLOps architecture for models: training, registry, serving, monitoring.
• Sets engineering standards for agent quality, safety, and observability.
• Develops secure production code for critical paths and reviews peers' work.
• Mentors engineers and raises the technical bar through architecture decisions.

Skills

Python

Java

Kubernetes

MLOps

Distributed Systems

Security

AI governance

Tools

Databricks

Git

Istio

Job description

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Senior Lead Software Engineer at JPMorganChase within the Commercial and Investment Bank, Payments Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As the senior technical authority for the London team, you set the architecture for our B2B agentic commerce agents and for how ML models are trained, served, and governed as tools those agents rely on. Your decisions shape how agents acting for buyers and suppliers can transact safely at the scale of a global bank.

Job Responsibilities

• Sets the technical direction and reference architecture for B2B agentic commerce: multi-agent topology, agent-to-agent (A2A) communication, tool integration over MCP, and the boundary between LLM reasoning and deterministic services
• Designs information barriers and authorization for agents that act on behalf of different counterparties, using fine-grained authorization and isolated execution where tenants may be adversarial
• Defines the MLOps architecture for models used as agent tools: training on Databricks, environment promotion, model registry, serving on Kubernetes, monitoring, and retraining cadence
• Sets engineering standards for agent quality and safety, including evaluation frameworks, guardrails, observability, and the evidence required for model risk approval
• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure and high-quality production code for critical paths, and reviews and debugs code written by others
• Partners with the NEO platform team to contribute reusable capabilities back to the platform, and with product, risk, and client-facing channel teams on external agent integration
• Drives team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Mentors lead and associate engineers, and raises the technical bar through design reviews and written architecture decisions

Required Qualifications, Capabilities, And Skills

• Formal training or certification on software engineering concepts and advanced applied experience
• Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s), with strong hands‑on experience in Python and/or Java required
• Deep understanding of concurrency and distributed computation, with proven experience designing multithreaded and multi‑process systems, worker and task‑queue architectures, and distributed workloads that are correct and observable under concurrency (consistency, idempotency, backpressure, partial failure)
• Proven experience architecting and shipping production LLM agents or multi‑agent systems, including tool use, memory, evaluation, and guardrails
• Proven experience designing end‑to‑end ML platforms or MLOps pipelines, from training through serving and monitoring
• Experience designing secure distributed systems, including identity, authorization, and service‑to‑service trust
• Demonstrated experience leading effective use of approved AI‑assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• In‑depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience
• Deep proficiency with Kubernetes and Amazon EKS, micro‑VM isolation (e.g., Firecracker, Kata Containers, gVisor), and sidecar architectures, with proven experience designing defense in depth across the stack: network and mTLS, workload identity, fine‑grained authorization, runtime isolation for untrusted or adversarial workloads, and application‑level guardrails

Preferred Qualifications, Capabilities, And Skills

• Deep experience with agent protocols and frameworks: MCP, A2A, AG-UI, Google ADK or LangGraph
• Experience with agent payment and mandate patterns (e.g., AP2), or with regulated workflows where LLM output must be constrained and auditable
• Experience with OpenFGA or OPA/Rego, service mesh (Istio/Envoy mTLS), and micro‑VM isolation (Kata, gVisor, Firecracker)
• Experience with Databricks, MLflow, and model serving on Kubernetes, including GPU capacity planning and small language model inference
• Experience with knowledge graphs, GraphRAG, or organizational memory for agents
• Experience with optimization, pricing, or negotiation models in a production setting
• Domain knowledge of B2B payments, commercial card, supplier enablement, or treasury

ABOUT US

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first‑class business in a first‑class way approach to serving clients drives everything we do. We strive to build trusted, long‑term partnerships to help our clients achieve their business objectives.

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. Visit our FAQs for more information about requesting an accommodation.

About The Team

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.