Lead Software Engineer, AI Foundation Services

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

• Formal training or certification in software engineering concepts, plus at least 5 years of applied experience
• Strong hands-on coding skills in one or more platform-service languages, such as Python, Java, or Go, and experience delivering production-grade services or APIs
• Experience building shared services, reusable components, or platform capabilities used by multiple application or engineering teams
• Experience with infrastructure as code and cloud-native delivery, including tools and practices such as Terraform, containers, Kubernetes, CI/CD pipelines, and automated deployments
• Experience leading the effective use of approved AI-assisted software development tools, and setting expectations for validating outputs for correctness, performance, and security
• Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and security and resiliency expectations; experience coaching engineers on safe, compliant adoption
• Practical experience with system design, application development, automated testing, debugging, and production software stability
• Experience implementing observability, logging, metrics, alerts, Service Level Objectives, incident response, and root-cause analysis for production services
• Working knowledge of software development and technical processes, with depth in areas such as cloud platforms, artificial intelligence, machine learning platforms, distributed systems, or infrastructure engineering
• Ability to translate technical requirements into actionable engineering tasks, manage dependencies, and deliver milestones with product and application teams
• Strong written and verbal communication skills, including the ability to explain technical decisions, trade-offs, issues, and risks to engineering teams and stakeholders
• Experience supporting AI/ML or GenAI platform capabilities, such as model hosting, inference services, model gateways, managed AI services, or developer-facing AI/ML infrastructure
• Experience with GPU-enabled platforms or AI workload optimization, including inference latency, throughput, batching, capacity planning, or cost and performance tuning
• Experience developing reusable templates, reference implementations, SDKs, automated tests, onboarding guides, or deployment patterns
• Familiarity with model-serving patterns, rollout strategies, safety controls, authorization, rate limiting, policy enforcement, and evaluation hooks

• Partner with Lines of Business application teams to implement AI Foundation Services that enable GenAI and AI use cases, supporting delivery from technical design through launch and early operational support
• Build and improve reusable platform services, APIs, SDKs, and libraries that standardize how application teams use model hosting, inference, and managed AI/ML services
• Turn functional and non-functional application requirements into technical designs, engineering tasks, and delivery milestones, working with senior engineers and architects
• Develop secure, stable, high-quality production code and participate in code reviews, debugging, testing, and defect remediation
• Create and maintain reusable engineering resources, including reference implementations, runbooks, test harnesses, baseline configurations, and onboarding guides
• Encourage effective use of enterprise-authorized AI-assisted engineering tools and practices to improve code quality, delivery speed, and operational outcomes; establish validation standards for secure coding, peer review, and automated testing, and promote effective patterns across the team
• Use Software Development Life Cycle tools, including authorized AI-assisted development and automation capabilities, to increase the value of automation
• Design and implement scalable software components using suitable design patterns, cloud-native practices, and platform engineering standards
• Work across product, architecture, security, infrastructure, and application development teams to resolve dependencies and deliver production-ready capabilities
• Contribute technical methods, standards, documentation, and implementation patterns that improve consistency, reliability, and reuse across AI Foundation Services teams
• Communicate technical progress, risks, dependencies, and implementation options to engineering managers, product partners, and senior technical stakeholders

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

More:

We are collaborating with hackajob to connect exceptional professionals with this Lead Software Engineer role on our Chief Data & Analytics (AIML Data Platforms) team in Jersey City. You will help build secure, reliable, cloud-native AI foundation services for GenAI and machine learning at enterprise scale as part of an agile team delivering trusted, stable, and scalable technology. We are one of the worlds longstanding financial institutions, serving consumers, small businesses, and corporate, institutional, and government clients through our J.P. Morgan and Chase brands. Our Corporate Functions teams support the success of our businesses, clients, customers, and employees. We offer competitive total rewards, with compensation based on role, experience, skills, and location; eligible roles may also include incentives. Benefits, subject to eligibility, include healthcare coverage, wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching. We value diversity and inclusion and provide reasonable accommodations in accordance with applicable law.

last updated 42 week of 2026