Lead AI Platform Engineer: Scalable, Secure Backend

JPMorgan Chase & Co.

Houston (TX)

On-site

USD 150,000 - 210,000

Full time

14 days+

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Job summary

JPMorgan Chase & Co. in Houston seeks a Lead Software Engineer to join the Global Banking Technology team, delivering scalable, secure technologies for deal origination, market intelligence, and client coverage.

You will be a core technical contributor crafting production-grade services and data flows across multiple platforms. You will design backend components with Java, Python, and React, mentor engineers, and advance AI-assisted development practices while ensuring reliability and security

Qualifications

Formal training or certification in software engineering concepts.
5+ years of applied software engineering experience.
Hands-on expertise across Java/J2EE, Spring Boot, and microservices.
Experience with AWS, Terraform, and modern DevOps tooling.
Experience using AI-assisted development tools and secure coding practices.
Strong understanding of relational and NoSQL databases.
Familiarity with monitoring/observability tools.
Ability to lead and mentor teams within a large corporate environment.

Responsibilities

Design and implement complex software components across backend services, APIs, and UI experiences using Java, Python, and React.
Build and refine agentic capabilities using the Smart SDK, including tool integration, orchestration patterns, and safety/reliability guardrails suitable for production use.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), 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.
Develop and optimize RAG pipelines end-to-end (ingestion, chunking, embeddings, retrieval, reranking, prompt/response patterns), improving relevance, latency, and robustness with OpenSearch and continuous measurement.
Write secure, high-quality production code and raise the bar through code reviews, debugging, and hands-on mentorship—improving maintainability, performance, and consistency across the codebase.
Drive operational excellence by identifying recurring issues and implementing automation, preventative controls, and reliability improvements to reduce toil and improve system stability.
Engineer data and search solutions using PostgreSQL (schema design, migrations, query tuning) and OpenSearch (indexing strategies, query relevance tuning) to support AI and analytics workflows
Contribute to cloud-native engineering on AWS, partnering on infrastructure-as-code with Terraform and improving deployment safety, environment consistency, and observability.
Participate in technical evaluation sessions with internal partners and external vendors—assessing architecture, technical depth, and fit within existing platforms and information architecture.
Champion modern engineering practices and knowledge-sharing, contributing to communities of practice and accelerating adoption of leading-edge technologies.