Director, Software Engineering

Fidelity Investments•Westlake, TX

1d•Hybrid

About The Position

Role Overview The Wealth Technology Gen AI Enablement team accelerates safe, scalable, and high‑impact adoption of Generative AI Dev Assist across Wealth Technology. The team focuses on engineering‑led enablement and enterprise‑scale program execution to integrate Gen AI developer assist capabilities across the Wealth Technology ecosystem, while elevating workforce skills and ensuring responsible adoption. This role aligns to the 2026 Gen AI Enablement vision (adoption & value realization, SDLC integration through partnership, workforce skill development, responsible AI, and metrics‑driven improvement). The role does not own the SDLC or platform engineering delivery, but is accountable for deep collaboration with Wealth Technology platform teams to ensure Gen AI Dev Assist is integrated consistently, securely, and effectively across the ecosystem. Director, Wealth Technology Gen AI Enablement The Director is a hybrid engineering leader and large‑scale program leader responsible for driving Gen AI enablement across Wealth Technology. This role requires deep technical credibility as an expert engineer, paired with the ability to orchestrate complex, fast‑moving programs that deliver value in short, iterative cycles spanning platform teams, engineering leaders, risk partners, and learning organizations. The Director serves as a collaborator and facilitator, not a gatekeeper — aligning teams, accelerating adoption, and ensuring Gen AI developer assist capabilities are embedded across the ecosystem through partnership rather than ownership. A core focus of the role is the ideation, design, and execution of a the Gen AI learning roadmap, elevating the capabilities of 4,000+ associates to use Gen AI tools quickly, securely, and effectively — both today and as the technology evolves. This is a hands‑on leadership role that balances strategy, execution, and selective deep technical engagement where leverage is highest.

Responsibilities

Engineering & Technical Leadership Act as an expert engineering voice on Gen AI‑assisted development, maintaining hands‑on understanding of modern Gen AI developer assist tools and workflows.
Partner with Wealth Technology platform and tooling teams to integrate Gen AI Dev Assist capabilities across the ecosystem, influencing design and standards through collaboration rather than direct ownership.
Identify and validate high‑value Gen AI use cases across the SDLC, ensuring they are practical, scalable, and aligned with engineering standards.
Program Leadership & Ecosystem Orchestration Lead large‑scale, cross‑organizational Gen AI enablement programs spanning multiple platforms, domains, and engineering organizations.
Coordinate dependencies, sequencing, and execution across platform teams, engineering leaders, security, risk, and architecture partners.
Translate enterprise Gen AI direction into actionable, phased roadmaps and execution plans for Wealth Technology.
Enablement Through Partnership Lead and support Gen AI enablement initiatives that elevate workforce effectiveness at scale, in close partnership with engineering leaders, platform teams, and the enterprise Learning organization.
Serve as a technical and enablement bridge to ensure guidance and learning experiences are practical, current, and aligned to real developer workflows.
Contribute to scalable approaches that enable 4,000+ associates to adopt Gen AI tools quickly, securely, and effectively as capabilities evolve.
Collaboration, Facilitation & Influence Serve as a trusted collaborator with engineering leaders, platform teams, and chapter leads to accelerate adoption without disrupting delivery.
Facilitate alignment across teams with differing priorities, constraints, and maturity levels.
Act as a trusted advisor to senior leaders on Gen AI readiness, progress, and adoption challenges.
Governance & Responsible AI Enablement Partner with risk, security, and architecture teams to operationalize responsible Gen AI guardrails through education, patterns, and practical guidance.
Proactively identify and mitigate risks such as shadow AI usage, inconsistent adoption, and long‑term technical debt.
Reinforce secure and compliant usage without creating friction for engineering teams.
Metrics & Value Realization Partner with our enterprise team to define and track metrics for adoption, productivity, quality, developer experience, and learning effectiveness.
Use insights to continuously refine enablement strategy, learning investments, and program sequencing.
Demonstrate durable value realization from Gen AI adoption at scale.