Director of Software Engineering- HR Technologies

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Director of Software Engineering in HR Technology – Talent Acquisition to lead an engineering organization responsible for a secure, scalable cloud-native Talent Acquisition platform.

You will own technology direction, drive modernization, and collaborate with HR Product, Experience Design, and Risk/Controls to deliver measurable outcomes. You will guide multiple cross-functional teams, oversee architecture, governance, and end-to-end delivery, and champion a

Qualifications

• 10+ years applied experience in software engineering leadership.
• Proven track record leading mission-critical platforms with high availability and measurable outcomes.
• Experience delivering modern web and API platforms (distributed systems, microservices).
• Strong knowledge of cloud-native engineering (AWS or equivalent), reliability, security and SDLC automation.
• Ability to influence senior stakeholders and communicate strategy and delivery status clearly.
• Hands-on understanding of security controls: identity/access, data privacy, secure SDLC, vulnerability management.
• Strong people leadership: hiring, mentoring, building inclusive teams.
• Experience adopting AI-enabled engineering practices with guardrails and governance.
• Understanding of responsible AI use and scalable, safe AI patterns.

Responsibilities

• Set engineering vision and roadmap for the Talent Acquisition platform.
• Lead multiple cross-functional engineering teams and manage org design and performance.
• Drive platform architecture and cloud-native modernization with reusable capabilities.
• Oversee end-to-end delivery, production readiness, incident management, and cost governance.
• Govern integrations with HR systems, analytics, and external TA vendors with secure patterns.
• Establish engineering governance: security standards, SDLC controls, and KPI tracking.
• Collaborate with Product, UX, and HR to translate strategy into outcomes.
• Manage vendor relationships, due diligence, and performance oversight.
• Foster an inclusion-driven, high-standard engineering culture; promote responsible AI usage.

Skills

Leadership

Strategic thinking

Cross-functional collaboration

Cloud-native engineering

Security controls

AI governance

Education

Software engineering degree

Certifications in software engineering concepts

Tools

AWS

REST API

GraphQL

Terraform

CI/CD

Job description

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 JPMorgan Chase within HR Technology – Talent Acquisition, you will lead a critical product-aligned engineering organization responsible for building and operating a secure, scalable, cloud-native Talent Acquisition platform. You will own technology direction and execution across multiple teams, drive modernization and integration strategy, and partner closely with HR Product, Experience Design, Risk/Controls, and senior stakeholders to deliver measurable outcomes.

Job Responsibilities

• Set engineering vision and roadmap execution for the Talent Acquisition platform, balancing user experience, time-to-market, reliability, and control obligations.
• Lead multiple cross-functional engineering teams (full stack, backend, platform/integration, SRE/operations as applicable), including org design, hiring, coaching, performance management, and succession planning.
• Drive platform architecture and modernization, including cloud-native patterns, domain-driven service boundaries, API/event strategy, and reusable platform capabilities.
• Own end-to-end delivery and operations, ensuring production readiness, incident management, reliability/SLOs, observability, cost governance, and continuous improvement.
• Oversee integrations into HR workforce and compensation systems, workflow tooling, identity/access systems, analytics, and external TA vendors; ensure resilient integration patterns and strong data contracts.
• Establish and enforce engineering governance: secure coding standards, architecture review, SDLC controls, change management, audit readiness, and measurable engineering KPIs (availability, latency, defect escape rate, lead time, cost to serve).
• Partner with Product, UX, and HR stakeholders to translate strategy into outcomes, manage trade-offs, and ensure solutions solve real business problems.
• Manage third-party vendor and platform relationships: due diligence, technical fit, security posture, delivery oversight, and commercial/operational accountability (in partnership with sourcing and product).
• Champion a strong engineering culture grounded in inclusion, accountability, high standards, and continuous learning; promote responsible use of AI-assisted development with appropriate guardrails.
• Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM 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.

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.
• Proven track record leading mission-critical platforms with high availability, strong operational excellence, and measurable outcomes.
• Experience delivering modern web and API platforms, including distributed systems, service-oriented architecture/microservices, and integration-heavy domains.
• Strong knowledge of cloud-native engineering (e.g., "AWS or equivalent"), including reliability, security, cost management, and SDLC automation.
• Demonstrated ability to influence and align senior business, product, and technology stakeholders, including communicating strategy, risks, and delivery status with clarity.
• Hands‑on understanding of engineering controls and security: identity/access management, data privacy, secure SDLC, vulnerability management, and audit/compliance expectations.
• Strong people leadership: hiring, mentoring, talent development, building inclusive/high-performing teams.
• Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human‑in‑the‑loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
• Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse.

Preferred Qualifications, Capabilities, and Skills

• Experience with HR technology and Talent Acquisition workflows, including ATS/CRM platforms, candidate pipelines, interview scheduling, offers, background checks, and onboarding.
• Proven ability integrating talent/HR applications with enterprise HR suites (e.g., "Oracle HCM" or similar) and broader vendor ecosystems.
• Familiarity with modern full-stack engineering, including React/TypeScript and enterprise design systems.
• Backend and API expertise with Java/Spring Boot, and strong GraphQL/REST API design, versioning, and governance practices.
• Solid security and data fundamentals, including OAuth2/OIDC, service-to-service security patterns, and data persistence (PostgreSQL/Aurora; graph stores like Neptune where applicable).
• Experience with event‑driven architectures using Kafka/MSK, including schema evolution, idempotency patterns, and operational controls (e.g., DLQs).
• Strong platform engineering and delivery practices: CI/CD, automated testing strategies, IaC (Terraform/CloudFormation/CDK), containers (ECS/EKS), plus establishing standards (service blueprints, API/event contract governance, SLO/SLI frameworks) and responsible AI‑assisted engineering practices (secure usage, quality gates, productivity enablement).