Senior Lead Software Engineer- Payments Tech - AI-First Developer Portal & External APIs

JPMorgan Chase & Co.•Jersey City, NJ

3d•$175,750 - $260,000

About The Position

This is your chance to shape an AI-first Developer Portal—a modern “front door” where clients and their systems can discover capabilities, onboard, troubleshoot, and integrate through agent-ready workflows and high-quality external APIs. As a Senior Vice President of Software Engineering within Payments Technology, you will lead teams and remain hands-on in building secure, stable, scalable platform capabilities that modernize the developer experience for the agentic era. As a Senior Lead Software Engineer at JPMorgan Chase within Payments Technology, you will lead teams and remain hands-on in building secure, stable, scalable platform capabilities that modernize the developer experience for the agentic era Role summary You will own the technical direction and execution for an AI-native portal experience where: Core portal capabilities are designed to be consumed by agents and automation (with excellent human UX as a companion). Workflows are exposed as reusable actions/tools with strong security, auditability, and operational controls. External API experiences are productized to be easy to discover, evaluate, and integrate—at scale.

Requirements

Formal training or certification in software engineering concepts and 5+ years applied experience; demonstrated coaching/mentoring experience.
10+ years of software engineering experience building and operating distributed systems at scale.
3+ years of experience leading software engineering teams and delivering complex platforms/products with measurable outcomes.
Strong hands-on backend development experience in Java (other modern backend stacks acceptable).
Proven expertise building external-facing APIs and integration platforms, including contract-first design, lifecycle/version management, security controls, and operational readiness.
Strong security fundamentals for external integrations: OAuth2/OIDC concepts, mTLS, PKI/certificates, secrets management, secure SDLC, and threat modeling.
Experience building AI-enabled product capabilities in production (beyond simple chat): grounded retrieval/search, structured tool/action execution, guardrails, evaluation practices, monitoring, and auditability.
Proficient in automation and continuous delivery methods; advanced understanding of agile and modern SDLC practices.
Strong understanding of application resiliency and observability (logs/metrics/traces), performance engineering, and incident management.
Experience working in regulated environments with strong controls, compliance requirements, and reliability expectations.

Nice To Haves

Developer portal or developer-experience platform experience (onboarding journeys, documentation-as-a-product, integration tooling, sandbox/test experiences).
Experience building workflow/orchestration systems (state machines, async processing, retries, compensating actions).
Search and relevance experience (enterprise search, ranking, contextual retrieval, content quality signals).
Cloud-native delivery experience (containers/Kubernetes) and event-driven architectures (webhooks/callbacks/streams).
Prior payments, treasury, or broader financial-services platform experience.

Responsibilities

Lead the creation of an AI-first Developer Portal experience: define architecture patterns for agent-ready workflows, tool/action schemas, context assembly, and safe execution.
Build and operate AI-enabled support experiences (assistant + workflow automation) with contextual understanding of client/workspace state, integration progress, and troubleshooting signals.
Design and deliver secure external API platform capabilities: contract-first API design (OpenAPI), versioning strategy, backward compatibility, idempotency, pagination, consistent error models, and developer usability.
Own authentication and credential workflows for external integrations, including patterns for certificate handling, credential rotation, and secure onboarding journeys.
Establish engineering standards for AI + automation in production: evaluation and test strategy, release gating, telemetry, audit logging, and incident response for AI/tooling systems.
Remain hands-on (~50%) through critical-path coding, architecture reviews, code reviews, debugging, and performance/resiliency improvements.
Drive cross-functional, federated delivery by partnering with API owners, security, and shared services to deliver a unified client experience despite distributed backend ownership.
Coach and develop engineers: set expectations for quality, delivery discipline, design rigor, and collaboration; actively grow technical talent and leadership bench.