{"id":922156,"url":"https://alion.io/job/jpmorganchase-lead-software-engineer-ai-foundation-services","title":"Lead Software Engineer-AI Foundation Services","company":{"id":257,"name":"JPMorganChase","domain":"jpmorganchase.com","url":"https://alion.io/company/jpmorganchase","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":88,"open_postings":1016,"ghost_share":0.009,"stale_share":0.628,"repost_share":0.048,"time_to_fill_p50_days":15,"computed_at":"2026-11-12T10:38:37Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Plano, United States","Wilmington, United States","Seattle, United States","Jersey City, United States","Palo Alto, United States","McLean, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":193000,"max_usd":401000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":782},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-07-14T00:00:00Z","employer_posted_date":"2026-07-14","last_verified_at":"2026-11-13T02:27:03Z","board_verified":true,"closed_at":null,"days_open":122,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":121},"description":"Join JPMorganChase’s Chief Data & Analytics (AIML Data Platforms) team in Jersey City as a Lead Software Engineer building AI foundation services for GenAI and ML at enterprise scale. You’ll lead hands-on delivery of secure, reliable, cloud-native platform capabilities (Kubernetes/CI/CD/IaC) and partner with application teams to create reusable integrations, reference implementations, and onboarding assets.\nAs a Lead Software Engineer at JPMorganChase within the AIML Data Platforms - Chief Data and Analytics team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. In this role you will get to drive significant business impact through your capabilities and contributions and apply your deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.\nJob responsibilities\nPartners 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\nBuilds and enhances reusable platform services, APIs, SDKs, and libraries that standardize how application teams consume model hosting, inference, and AI/ML managed services\nTranslates functional and non-functional application requirements into clear technical designs, engineering tasks, and delivery milestones with support from senior engineers and architects\nDevelops secure, stable, and high-quality production code, and participates in code reviews, debugging, testing, and remediation of defects across AI Foundation Services components\nCreates and maintains reusable engineering assets such as reference implementations, runbooks, test harnesses, baseline configurations, and onboarding guides to accelerate adoption across teams\nDrives 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.\nApplies 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.\nDesigns and implements scalable software components using appropriate software design patterns, cloud-native practices, and platform engineering standards\nCollaborates with cross-functional teams across product, architecture, security, infrastructure, and application development to resolve technical dependencies and deliver production-ready capabilities\nContributes to technical methods, standards, documentation, and implementation patterns within AI Foundation Services, helping improve consistency, reliability, and reuse across delivery teams\nCommunicates technical progress, risks, dependencies, and implementation options to engineering managers, product partners, and senior technical stakeholders \nRequired qualifications, capabilities, and skills\nFormal training or certification on software engineering concepts and 5+ years applied experience\n\nStrong hands-on coding experience in one or more languages used for platform services, such as Python, Java, or Go, with experience delivering production-grade services or APIs\nExperience building shared services, reusable components, or platform capabilities consumed by multiple application or engineering teams\nExperience with infrastructure-as-code and cloud-native delivery practices, including tools such as Terraform, containers, Kubernetes, CI/CD pipelines, and automated deployment workflows\nDemonstrated 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\nStrong 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\nHands-on practical experience with system design, application development, automated testing, debugging, and operational stability for production software\nExperience implementing observability, logging, metrics, alerts, Service Level Objectives, incident response practices, and root-cause analysis for services in production\nWorking 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\nAbility to break down technical requirements into executable engineering tasks, manage dependencies, and deliver against milestones in partnership with product and application teams\nStrong written and verbal communication skills, with the ability to explain technical decisions, trade-offs, issues, and risks to engineering teams and stakeholders \nPreferred qualifications, capabilities, and skills\nExperience supporting AI/ML or GenAI platform capabilities, including model hosting, inference services, model gateways, managed AI services, or developer-facing AI/ML infrastructure\nExperience with GPU-enabled platforms or AI workload optimization, including inference latency, throughput, batching, capacity planning, or cost/performance tuning\nExperience building reusable “golden path” assets such as templates, reference implementations, SDKs, automated tests, onboarding guides, and deployment patterns\nFamiliarity with model serving patterns, rollout strategies, safety controls, authorization, rate limiting, policy enforcement, and evaluation hooks","description_format":"text","description_chars":6139,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Wealth Management & Financial Advisors","Asset Management & Funds","Investment Banking & M&A 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