Senior Lead Software Engineer, AI Services

Salary: $61,000 - 101,000 per year Requirements:

• Formal software engineering training or certification, plus 5+ years of practical experience
• Hands-on background designing, building, testing, and running production software systems, distributed services, or platform capabilities
• Practical exposure to AI/ML platform services, including model serving, model hosting, data access patterns, platform integrations, or infrastructure support for AI/ML workloads
• Experience developing cloud-native applications or platform services with Kubernetes, containers, CI/CD, infrastructure as code, and modern engineering practices
• Proficiency in one or more programming languages such as Python, Java, Go, or similar, with a track record of delivering quality production code
• Experience turning business or application team needs into technical designs, delivery tasks, milestones, and support plans
• Working knowledge of performance engineering and production reliability practices, including load testing, capacity planning, monitoring, alerting, SLOs/SLIs, incident response, and root-cause analysis
• Experience applying secure-by-design practices, including access controls, secrets management, vulnerability remediation, and secure handling of sensitive data
• Demonstrated use of enterprise-approved AI-assisted software development tools, with the ability to set 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 and outputs, and resiliency and security expectations
• Demonstrated ability to collaborate across product, application, infrastructure, and security teams to deliver complex technical outcomes
• Experience building or integrating GPU-backed model hosting, inference, training, or batch processing platforms
• Experience with LLM and model serving patterns, including routing, autoscaling, model gateways, inference optimization, evaluation workflows, and guardrail integration
• Experience optimizing AI/ML workloads for latency, throughput, reliability, and cost through profiling, batching, caching, concurrency tuning, and capacity modeling
• Experience creating reusable developer enablement assets such as golden paths, reference architectures, deployment templates, onboarding playbooks, automated test harnesses, and operational runbooks

• Design, build, integrate, and optimize AI Foundation Services infrastructure components for GenAI and traditional AI/ML platforms, with a focus on production-quality delivery and hands-on engineering
• Partner with Lines of Business application teams to co-develop reusable AI/ML foundation services, managed service integrations, and platform adoption patterns
• Translate application requirements into technical designs, implementation plans, and engineering deliverables that support launch and early operational readiness
• Help reduce delivery risk across performance, scale, reliability, and security by contributing to non-functional requirements, test plans, runbooks, observability, and production readiness reviews
• Build reusable engineering assets such as reference implementations, deployment templates, test harnesses, onboarding guides, and GPU/training/serving baselines for model hosting platforms
• Drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes
• Apply tools within the software development lifecycle toolchain, including approved AI-assisted development and automation capabilities, to increase automation value at scale
• Implement durable, maintainable code solutions and production platform capabilities that can be reused by multiple application teams and extended by other engineers
• Collaborate with product, platform, security, infrastructure, and application teams to resolve complex technical issues and deliver AI Foundation Services aligned to business priorities
• Take part in technical design reviews, operational readiness reviews, incident analysis, and continuous improvement activities to strengthen reliability, scalability, and developer experience

• AI
• CI/CD
• Cloud
• Support
• Java
• Kubernetes
• LLM
• Machine Learning
• Marketing
• Model Serving
• Python
• Security

More:

hackajob is partnering with J.P. Morgan to connect exceptional professionals with this Senior Lead Software Engineer opportunity in Jersey City on JPMorganChases Chief Data & Analytics (AIML Data Platforms) team. We are building AI foundation services for GenAI and machine learning at enterprise scale, with a focus on secure, reliable, cloud-native platform capabilities and reusable integrations that support application teams. JPMorganChase is one of the worlds oldest financial institutions, serving consumers, small businesses, corporate, institutional, and government clients through the J.P. Morgan and Chase brands. We offer a competitive total rewards package, with base salary based on role, experience, skills, and location, and eligible roles may include incentive compensation. Our benefits can include comprehensive health care, wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, financial coaching, and more. We value diversity and inclusion, and we are an equal opportunity employer that provides reasonable accommodations where needed. Our Corporate Functions team spans finance, risk, human resources, marketing, and other essential areas that help set our business, clients, customers, and employees up for success.

last updated 40 week of 2026