JPMorganChase Logo

JPMorganChase

Lead Software Engineer - AI Platform Reliability

Posted Yesterday
Be an Early Applicant
Hybrid
Seattle, WA, USA
Senior level
Hybrid
Seattle, WA, USA
Senior level
Lead design and delivery of reliable, scalable AI/ML platform services. Build production-grade code, reusable APIs/SDKs, observability and resilience tooling, define reliability standards, support on-call incident resolution, and mentor engineers to enable secure, compliant generative AI use cases.
The summary above was generated by AI

Are you passionate about building resilient, scalable systems that power the future of AI? At JPMorganChase, we're pushing the boundaries of what's possible with artificial intelligence and machine learning — and we need engineers like you to help us do it reliably, securely, and at scale.


As a Lead Software Engineer at JPMorganChase within the AI/ML Data Platforms organization, you will be a key member of the Reliability Engineering team, driving the design and delivery of trusted, market-leading technology products. You will apply your deep technical expertise and problem-solving skills to enhance the reliability and scalability of AI/ML platforms, build reusable services and tooling, and partner across teams to unblock high-impact AI use cases. This is an opportunity to shape how the firm delivers AI capabilities — with operational excellence at the core.


Job responsibilities

  • Design and implement solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast-growing demands
  • Develop secure, stable, and high-quality production code, and participate in code reviews, debugging, testing, and remediation of defects across AI Foundation Services components
  • Build and enhance reusable platform services, APIs, SDKs, and libraries that standardize how application teams consume model hosting, inference, and AI/ML managed services
  • Partner with Lines of Business application teams to implement AI Foundation Services capabilities that unblock generative AI and AI use cases, supporting delivery from technical design through build, launch, and early operational support
  • Own and evolve non-functional requirements and build/enhance tooling for observability, resilience, security controls, infrastructure management, and cost optimization
  • Establish and enforce standards and reference architectures for reliability, observability, automation, and operational readiness across services
  • Partner with product and platform engineering teams to define and meet service reliability targets, including performance, availability, and recoverability
  • Participate in on-call rotations, debug and resolve complex production issues; identify systemic gaps and drive durable remediation
  • Mentor and guide engineers; raise the bar on engineering quality, documentation, and operational rigor

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Strong hands-on coding experience in Python with experience delivering production-grade services
  • 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/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Hands-on practical experience with system design, automated testing, debugging, and operational stability for production software
  • Experience implementing observability, logging, metrics, alerts, Service Level Objectives, incident response practices, and root-cause analysis for services in production
  • Working knowledge of software application development and technical processes, with depth in one or more areas such as cloud platforms, artificial intelligence, machine learning platforms, distributed systems, or infrastructure engineering
  • Ability to break down technical requirements into executable engineering tasks, manage dependencies, and deliver against milestones in partnership with product and application teams
  • Strong written and verbal communication skills, with the ability to explain technical decisions, trade-offs, issues, and risks to engineering teams and stakeholders

Preferred qualifications, capabilities, and skills

  • Experience supporting AI/ML or generative AI platform capabilities, including model hosting, inference services, model gateways, managed AI services, or developer-facing AI/ML infrastructure
  • Proven skills in managing AI infrastructure on cloud platforms including deployment, scaling, monitoring, and optimizing machine learning workloads
  • Experience building reusable "golden path" assets such as templates, reference implementations, SDKs, automated tests, onboarding guides, and deployment patterns
  • Experience developing generative AI applications/AI agents and/or implementing AI-assisted operations with appropriate guardrails


#CTC

About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

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.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

About the TeamOur professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Similar Jobs

Yesterday
Hybrid
Seattle, WA, USA
Senior level
Senior level
Financial Services
Lead architecture and development of production-grade agentic AI and multi-agent systems for reliability engineering. Design autonomous agents, manage AI infrastructure and deployment, ensure observability/security/guardrails, automate remediation, evaluate vendors and models, and produce secure, high-quality production code to improve system reliability and engineering productivity.
Top Skills: Ai Agent FrameworksAWSCrewaiGenerative AiLanggraphPythonRetrieval-Augmented GenerationTerraformVector Search
16 Hours Ago
In-Office
Seattle, WA, USA
201K-251K Annually
Senior level
201K-251K Annually
Senior level
Artificial Intelligence • Cloud • Software • Infrastructure as a Service (IaaS)
Lead and mentor a multidisciplinary engineering team to build and deliver scalable security products (IAM, threat detection, data protection). Drive technical roadmap, manage delivery timelines and inter-team dependencies, prioritize technical debt, ensure code quality and security best practices, collaborate with product and security architects, and handle recruitment and career development.
Top Skills: Apache FlinkAWSAzureChefCryptographyGCPGoHelmIds/IpsJavaScriptKafkaKubernetesNode.jsSIEMTerraformVulnerability ScannersWaf
16 Hours Ago
In-Office
Seattle, WA, USA
159K-199K Annually
Senior level
159K-199K Annually
Senior level
Artificial Intelligence • Cloud • Software • Infrastructure as a Service (IaaS)
Manage the execution of Security Products by translating customer needs into requirements, collaborating with engineering and UX, and ensuring consistent communication for product launches and incidents.
Top Skills: CloudIamSaaSSecurity

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Amazon, Microsoft, Meta, Google
  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account