About this opportunity
JPMorgan Chase lists this Lead Software Engineer-AI Foundation Services opportunity in plano, Texas. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Job responsibilities
Partners with Lines of Business application teams to implement AI Foundation Services capabilities that unblock GenAI/AI use cases, supporting delivery from technical design through build, launch, and early operational support
Builds and enhances reusable platform services, APIs, SDKs, and libraries that standardize how application teams consume model hosting, inference, and AI/ML managed services
Translates functional and non-functional application requirements into clear technical designs, engineering tasks, and delivery milestones with support from senior engineers and architects
Develops secure, stable, and high-quality production code, and participates in code reviews, debugging, testing, and remediation of defects across AI Foundation Services components
Creates and maintains reusable engineering assets such as reference implementations, runbooks, test harnesses, baseline configurations, and onboarding guides to accelerate adoption across teams
Drives team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, establishing consistent validation standards and promoting reuse across the team
Applies knowledge of tools within the Software Development Life Cycle toolchain to improve automation value realization
Designs and implements scalable software components using appropriate design patterns, cloud-native practices, and platform engineering standards
Collaborates with cross-functional teams across product, architecture, security, infrastructure, and application development to resolve dependencies and deliver production-ready capabilities
Contributes to technical methods, standards, documentation, and implementation patterns within AI Foundation Services, improving consistency, reliability, and reuse across delivery teams
Communicates technical progress, risks, dependencies, and implementation options to engineering managers, product partners, and senior technical stakeholders
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Strong hands‑on coding experience in one or more languages such as Python, Java, or Go, delivering production‑grade services or APIs
Experience building shared services, reusable components, or platform capabilities consumed by multiple teams
Experience with infrastructure‑as‑code and cloud‑native delivery practices, including Terraform, containers, Kubernetes, CI/CD pipelines, and automated deployment workflows
Demonstrated experience leading the use of approved AI‑assisted development tools, setting expectations for validating AI outputs for correctness, performance, and security
Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure input/output handling, and adherence to security expectations; experience coaching engineers on safe, compliant adoption
Hands‑on experience with system design, application development, automated testing, debugging, and operational stability for production software
Experience implementing observability, logging, metrics, alerts, Service Level Objectives, incident response, and root‑cause analysis for production services
Working knowledge of software application development and technical processes, with depth in cloud platforms, AI/ML platforms, distributed systems, or infrastructure engineering
Ability to break down technical requirements into executable engineering tasks, manage dependencies, and deliver milestones in partnership with product and application teams
Strong written and verbal communication skills, explaining technical decisions, trade‑offs, issues, and risks to teams and stakeholders
Preferred qualifications, capabilities, and skills
Experience supporting AI/ML or GenAI platform capabilities, including model hosting, inference services, model gateways, managed AI services, or developer‑facing AI/ML infrastructure
Experience with GPU‑enabled platforms or AI workload optimization, inference latency, throughput, batching, capacity planning, or cost/performance tuning
Experience building reusable "golden path" assets such as templates, reference implementations, SDKs, automated tests, onboarding guides, and deployment patterns
Familiarity with model serving patterns, rollout strategies, safety controls, authorization, rate limiting, policy enforcement, and evaluation hooks
Benefits
We offer a competitive total rewards package including base salary determined by role, experience, skill set and location, commission‑based pay, discretionary incentive compensation, and a range of benefits such as health care coverage, wellness centers, retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching, and more.
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.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans.
Base Pay/Salary
Jersey City,NJ $152,000.00 - $215,000.00 / year
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Worksite address
plano, TX, 75086, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.