About The Role

If you are a software engineering leader ready to take the reins and drive impact, we’ve got an opportunity just for you.

As a Director of Software Engineering at JPMorganChase within Commercial & Investment Bank , Sales & Controls Tech Team, you lead a technical area and drive impact within teams, technologies, and projects across departments. Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.

Job responsibilities

Leads technology and process implementations to achieve functional technology objectives
Accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
Sets direction and governance for agentic AI-enabled engineering and SDLC/ADLC automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams.
Applies 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 and support capacity unlock initiatives at scale.
Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
Delivers technical solutions that can be leveraged across multiple businesses and domains
Leadership capabilities: leads/mentors technologists, influences stakeholders, and supports hiring/screening for deep technical roles.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
Expert Python engineer: builds production-grade services/libraries with strong testing, performance, and reliability practices.
Proven AI/agentic workflow architecture experience (tool-use patterns, orchestration, context management, guardrails, human-in-the-loop).
Strong solution/enterprise architecture skills: designs end-to-end systems and documents patterns, integrations, and data flows clearly.
Hands-on AWS experience delivering secure, scalable cloud-native services (IAM/security, networking, compute, monitoring/observability).
VectorDB + retrieval (RAG) experience: embedding/indexing pipelines, similarity search, metadata filtering, and relevance/latency tradeoffs.
Experience building personalization driven by user profiles/entitlements/preferences and applying it to AI assistant experiences.
Familiarity with voice + chat conversation data processing pipelines to enable assistant insights and personalization.
Platform ownership mindset for large user bases (~3,000 users): availability, resiliency, incident response, and safe release practices.
Strong responsible AI / controls understanding: secure handling of sensitive inputs/outputs, governance, and quality gates using enterprise-authorized tools.