Senior Director of Software Engineering, CI&A Agentic Identity & Lifecycle Lead

JPMorgan Chase

Confirmed live 2 days ago Low trust

Quick summary

Work type: On-site
Location: New York, NY
Posted: 35 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $220k

$158k most similar roles pay here $277k

This listing doesn't post a salary. Most similar roles pay $178,625–$260,725.

Based on 239 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Senior Director of Software Engineering, CI&A Agentic Identity & Lifecycle Lead

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As the Senior Director of Software Engineering - CI&A Agentic Identity & Lifecycle Lead within Connected Commerce Technology, you will lead multiple technical areas and manage several departments to drive firmwide technology objectives. You will be responsible for scaling multi-department strategies for agentic AI-enabled engineering and SDLC/TLM automation while establishing guardrails for security, reliability, and traceability. Your daily work involves managing complex projects, influencing senior stakeholders, and overseeing large cross-functional teams of technologists. The role requires expertise in identity and access management (IAM), including OAuth 2.0, OpenID Connect, and token-based authorization frameworks. You will specifically focus on securing agentic AI systems, defining non-human principal identities, and managing lifecycle policies for automated workflows. Required skills include cloud native experience, knowledge of Model Context Protocol, and expertise in ensuring responsible AI risk controls within distributed environments.

Skills

Agentic AI SDLC IAM OAuth 2.0 OpenID Connect Token-based Authorization Cloud Native Model Context Protocol Resilience Engineering Incident Response System Design Machine-to-Machine Trust

What you'll do

Lead multiple technology and process implementations across departments to achieve firmwide objectives.
Set and scale multi-department strategies for agentic AI-enabled engineering and SDLC automation.
Establish guardrails for validation, security, resiliency, traceability, and reuse in automated workflows.
Drive cross-domain reuse and capacity gains using enterprise-authorized AI-assisted development tools.
Act as the primary interface with senior leaders and stakeholders to drive consensus across competing objectives.
Define identity, authentication, and authorization models for non-human principals at enterprise scale.
Advise senior leadership on responsible AI risk, controls, and safe adoption strategies.
Manage large cross-functional teams of technologists while overseeing hiring and talent development.

What we're looking for

Formal training or certification in software engineering concepts and 10+ years of applied experience.
5+ years of experience leading technologists to manage and solve complex technical items within a domain of expertise.
Demonstrated expertise in identity and access management, including OAuth 2.0, OpenID Connect, and token-based authorization frameworks.
Practical experience securing agentic AI systems and defining authentication models for non-human principals at enterprise scale.
Experience leading multi-organization adoption of agentic AI-enabled engineering operating models and related governance frameworks.
Deep understanding of responsible AI risk, controls, and security expectations to advise senior leaders on safe adoption.
Extensive practical cloud native experience.
Experience with hiring, developing, and recognizing talent.
Working knowledge of delegated authorization patterns, token exchange flows, and least-privilege scope models (preferred).
Exposure to verifiable credential frameworks or decentralized identity concepts for machine-to-machine trust (preferred).
Experience defining lifecycle management policies for non-human identities (preferred).

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