SR Principal Software Engineer - Applied AI Engineering

Join the ranks of top talent at one of the world's most influential companies as a tech leader delivering AI-powered solutions across the software and product development lifecycles.

About the role

As Senior Principal Software Engineer within the Commercial and Investment Bank Payments Technology team, you will focus on delivering robust, secure, and scalable engineering outcomes by embedding AI into production workflows. This role requires deep expertise in software engineering, AI/LLMs, agentic development patterns, and a strong track record in delivery. You will influence outcomes across a highly matrixed organization, ensuring successful adoption and continuous improvement of AI-enabled engineering practices. Leading multiple technical areas, you will manage cross-functional initiatives, drive alignment with stakeholders, and set strategy for AI-native SDLC and TLM automation.

Responsibilities

• Lead the execution of an AI-native SDLC and PDLC model across architecture, coding, security, testing, release, and observability phases.
• Operationalize agentic patterns and toolchains, including LLM orchestration, skills, context engineering, and MCP-based integrations.
• Ensure responsible AI practices in production: guardrails, evaluation, monitoring, and auditable workflows.
• Partner with App Dev leaders and platform owners to identify high-impact use cases, validate value, and scale production adoption.
• Translate engineering workflows into AI-enabled production capabilities (assistive to autonomous) that materially reduce developer toil.
• Drive alignment with GT/LOB stakeholders on control design, security approvals, platform standards, and rollout approach.
• Lead multiple technology and process implementations across departments to achieve firmwide technology objectives.
• Interface with senior leaders, stakeholders, and executives, driving consensus across competing objectives.
• Set and scale multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation to drive firmwide objectives (speed, scalability, reliability, and cost-to-serve).
• Establish portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, and incident response acceleration.
• Define guardrails for validation, security, resiliency, traceability, and reuse.
• Apply knowledge of SDLC toolchains, including enterprise-authorized AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes.

Requirements

• Formal training or certification on software engineering concepts and 10+ years of applied experience.
• Deep expertise in AI/LLMs and their application to software engineering workflows (coding, design, security, testing, release).
• Hands-on experience with agentic systems, tool/skill orchestration, and integration patterns (e.g., MCP, A2A, function/tool calling).
• Proven ability to lead cross-functional engineering delivery amid ambiguity, including roadmap definition, backlog, dependency management, and stakeholder alignment.
• Strong communicator with executive-level stakeholder management, able to translate between engineering depth and business outcomes.
• Experience leading multi-organization adoption of agentic AI-enabled engineering operating models, including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs.
• Demonstrated experience influencing across highly matrixed, complex organizations and delivering value at scale.
• Experience leading complex projects supporting system design, testing, and operational stability.
• Experience with hiring, developing, and recognizing talent.
• Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.
• Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field.

Preferred Qualifications

• Experience working at code level.
• Experience with on-prem, cloud-native ecosystems and AWS services (e.g., EKS, Glue, S3).
• Familiarity with modern data architectures and sharing patterns, data contracts/entitlements, and cost optimization.
• Experience with secure SDLC practices and developer security tooling and vulnerability management metrics.
• API-first production design and integration patterns; strong analytics and experimentation discipline.

Benefits

• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support and financial coaching.

Pay

Competitive total rewards package including base salary determined based on the role, experience, skill set, and location. 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.

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.

About The Team

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services, and payments. Corporations, governments, and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk, and extends liquidity in markets around the world.