Design and deliver cloud-native platforms for product intake, communication, collaboration, roadmaps, and technical knowledge sharing as part of an agile engineering organization.
As a Senior Lead Software Engineer at JPMorganChase within the Chief Technology Office team, you will shape architecture and drive delivery across the firm's state-of-the-art technology products in a secure, stable, and scalable way. You'll set technical direction, lead complex initiatives end-to-end, and mentor engineers across teams, ensuring consistent design standards, robust operational practices, and measurable business outcomes. In this role, you'll join an agile engineering organization building and operating a growing portfolio of firmwide platforms: Feature Request, Convey, TechTube, go/roadmaps, go/blogs, and go/engineers, that streamline product intake, customer communication, knowledge sharing, roadmap transparency, long-form technical publishing, and developer documentation across the organization. You'll take ownership of one or more technical teams within this portfolio while influencing cross-platform strategy, architectural decisions, and the full SDLC to deliver scalable, cloud-native capabilities that improve transparency, collaboration, and value delivery for product teams firmwide. Given the common technology stack, cross-team contribution is expected, and you'll frequently lead initiatives spanning multiple products.
Job Responsibilities
- Own platform-level architecture and technical strategy across one or more platforms ensuring secure, scalable, and resilient solutions across the SDLC.
- Lead complex technical initiatives from discovery and design through delivery and operations, establishing engineering standards, reusable patterns, and reference implementations for cross-team adoption—including capability-first API designs that let multiple channels (authoring app, MCP, email, RSS, go/engineers) light up from a single investment.
- Design and implement complex, cloud-native software with clear ownership of key integrations, including Jira (Jira Align/Jira Plan for roadmap data), Bitbucket/GitHub (commit aggregation and contributor tracking), and event-driven notification and delivery workflows.
- Architect and build backend services, GraphQL APIs, and modern React UIs, including Module Federation micro-frontends and Hugo-based static content pipelines, ensuring thoughtful API design (GraphQL and REST) and robust client-server contracts.
- Own content and discovery capabilities such as Lucene-based full-text search, documentation hosting across 50+ content modules, and content authoring pipelines (scaffolding, validation, build), with an emphasis on the go/blogs and go/engineers merge track.
- Write secure, high-quality, well-documented code across multiple languages and frameworks (e.g., Java Spring Boot, React.js, GraphQL, Python, Go) while modeling best-in-class engineering practices.
- Mentor and grow engineers (junior through senior) through design reviews, code reviews, and hands-on guidance on best practices, system design, and implementation and partner with Product Owners and stakeholders to translate business goals into measurable technical outcomes, define roadmaps, and drive transparency through product metrics and KPIs.
- Set and enforce non-functional standards (security, performance, availability, observability, cost efficiency), including SLOs/SLAs, error budgets, automated quality gates in CI/CD, and consistent application of ADFS-based SSO and role-based access control across platforms.
- Evaluate and introduce new technologies to improve developer experience, platform quality, and delivery velocity; lead proofs of concept; and promote secure-by-design patterns, threat modeling, and proactive risk identification to meet firm standards and industry best practices.
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Proven expertise in distributed system design, application architecture, and technical leadership, including setting standards and leading cross-team initiatives.
- 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, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption.
- Strong experience developing, debugging, and maintaining code in large enterprise environments using modern programming and database querying languages.
- Hands-on proficiency in Java, JavaScript/TypeScript, and Python, with a track record of designing and delivering robust APIs (GraphQL and REST).
- Deep experience across the full SDLC with an emphasis on secure, resilient, and observable systems; AWS and cloud-native architectures (e.g., ECS/Fargate, SNS, SQS, Lambda, API Gateway, S3), including multi-AZ/multi-region resiliency design.
- Strong understanding of agile methodologies and practices such as CI/CD, application resiliency, and security; ability to drive continuous improvement in engineering workflows.
- Demonstrated ability to mentor engineers, lead design reviews, and guide architectural decisions that improve reliability, performance, and developer productivity.
- Advanced knowledge within one or more technical disciplines (e.g., cloud, AI/ML, mobile, data platforms) and the ability to apply it pragmatically in product contexts.
- Excellent communication and stakeholder management skills, with experience aligning technical decisions to business outcomes and product strategy.
Preferred Qualifications, Capabilities, and Skills
- Infrastructure as Code expertise using Terraform, with modular patterns and guardrails.
- Experience with relational and distributed databases (PostgreSQL a plus), including data modeling, performance tuning, and operational considerations along with video streaming, content management, or media platforms (a plus), including performance and caching strategies.
- Strong background in observability and performance optimization (metrics, logging, tracing) and cost governance for cloud workloads.
- Experience with static site generators (Hugo) and content pipelines, including static builds, module registries, and artifact publishing (e.g., Artifactory), Lucene or similar full-text search, including indexing, filters, and tag-based discovery.
- Experience building micro-frontends via Module Federation and integrating them into host platforms, building Go CLI tools for scaffolding, validation, and build automation.
- Experience with content authoring and publishing platforms, RSS/email delivery channels, and MCP (Model Context Protocol) channels for agent/IDE integration, ADFS-based SSO and role-based access control, integrating with Bitbucket/GitHub for contributor and commit tracking