Leads platform engineering across distributed systems, shared libraries, cloud execution layers, and service contracts. Sets architecture and engineering standards, improves model execution performance, governs AI-assisted development practices, and drives CI/CD, testing, security, observability, and versioning. Mentors engineers, leads code reviews, resolves complex production incidents, coordinates cross-team changes, and translates business needs into technical roadmaps.
Join us as a Senior Technical Lead and help build the backbone of our platform. You’ll set technical direction, raise engineering standards, and stay hands-on with design and reviews that impact multiple codebases. This is your opportunity to tackle real-world performance challenges, collaborate with talented engineers, and influence the future of our technology. If you thrive on solving complex problems and mentoring others, this role is for you.
Job Summary:
As a Senior Technical Lead in the Platform Engineering team, you will own the technical direction across services and shared libraries. You will define and evolve architecture contracts between the UI, backend services, shared libraries, and cloud execution layers. You will drive execution performance improvements, set engineering standards, and coordinate change across teams and codebases. You will mentor engineers, lead high-impact code reviews, and serve as the escalation point for challenging production incidents. You will partner with stakeholders to translate business requirements into a clear technical roadmap.
Job Responsibilities:
- Own cross-cutting architecture by defining and evolving contracts between UI, backend services, shared libraries, and cloud/compute execution layers
- Drive execution performance improvements by tackling model start-up latency and warm/pooled compute, evaluating instance pools, serverless, and warm-executor patterns
- 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,
- Set engineering standards for testing strategy, CI/CD, secure-by-default practices, observability, and backwards-compatible versioning across shared libraries
- Coordinate change across teams and codebases by breaking features into well-scoped, contract-first workstreams and aligning API/schema changes
- Mentor mid/senior engineers, run high-signal code reviews, and be the escalation point for complex production incidents
- Partner with stakeholders to translate user and business requirements into a pragmatic technical roadmap
- Design and review changes that span multiple services and shared libraries to ensure correctness, performance, and maintainability
- Establish and maintain a clear, documented architecture and contract map that enables new engineers to quickly navigate the platform
- Achieve measurable improvements in execution start-up time for smaller models, enhancing overall system efficiency
Required Qualifications, Capabilities, and Skills:
- Significant experience building and operating production software as a technical lead on distributed systems
- Deep expertise in Python and FastAPI/REST, including async patterns and SQLAlchemy
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
- Strong AWS background, including serverless orchestration (Step Functions/Lambda), container deployment (ECS/EKS), and managed data services
- Proven track record designing and evolving service-to-service contracts without breaking consumers
- Solid grasp of CI/CD, automated testing, and secure-by-default engineering (secrets, IAM, least privilege)
- Ability to lead across teams and communicate clearly with engineers and business stakeholders
Preferred Qualifications, Capabilities, and Skills:
- Experience with Databricks/Spark and ML/forecasting execution at scale, including optimizing cold-start/warm-compute
- Familiarity with TypeScript/React micro-frontends (Module Federation) to guide UI direction
- Ownership of Terraform and infrastructure-as-code
- Experience with model governance/SDLC (approval flows, audit, environment promotion) in a regulated setting
- Background in financial services or other compliance-heavy environments
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.
JPMorganChase London, England Office
25 Bank Street, Canary Wharf, London, United Kingdom, E14 5JP
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