Vice President of Software Engineering

THE PHOENIX

United States

11 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

3 years minimum

Working hours

Regular working hours

Job source

arc.dev

Tech stack

JavaScript (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Data Analysis Computing Platforms Automation of Tests Microsoft Azure Cloud Computing Code Coverage Software Quality Code Review

+19 more

Continuous Integration Cursor (Graphical User Interface Elements) Programming Tools Github Industry Standard Architecture Python (Programming Language) Systems Development Life Cycle Release Management Secure Coding Software Engineering TypeScript Software Vulnerability Management Enterprise Software Applications GitHub Copilot Software Security Github Enterprise Software Version Control Static Application Security Testing Dynamic Application Security Testing

Job description

Establish and evolve organization-wide software engineering standards and practices across the full SDLC, including software design, source control, code review, testing, CI/CD, security, documentation, release management, and production readiness.
Build a strong software engineering culture, establishing clear expectations around code quality, testing rigor, design reviews, architectural discipline, and engineering craftsmanship.
Lead the strategy, design, and development of the firm’s internal developer platform and developer tooling, treating developer experience as a product and creating scalable golden paths, self-service capabilities, frameworks, and tooling that make it easier for engineers to build high-quality software.
Own Developer Experience and Engineering Effectiveness, identifying friction throughout the development lifecycle and improving developer productivity, cycle time, PR quality, test coverage, deployment frequency, and overall software delivery performance.
Define how AI-assisted development integrates into the software engineering lifecycle, balancing the speed and productivity benefits of agentic coding with the engineering rigor required to safely ship production software.
Establish standards and guardrails for AI-generated and AI-assisted code, including expectations for code review, testing, documentation, security, architectural alignment, and human oversight.
Lead the adoption and governance of AI-powered developer tools such as GitHub Copilot, Cursor, Claude Code, and emerging agentic development platforms, developing repeatable workflows that improve engineering productivity without compromising software quality.
Develop an opinionated framework for human + AI software development, defining where AI can accelerate prototyping, implementation, testing, documentation, and code review-and where traditional engineering discipline and human judgment remain essential.
Lead the creation and governance of architecture review processes, including Architecture Decision Records (ADRs), design reviews, reference architectures, and architectural guardrails for critical systems and technical decisions.
Own and evolve source control, CI/CD, testing, and developer workflow standards, including GitHub Enterprise and GitHub Advanced Security, with an emphasis on creating an effective and secure developer experience.
Partner with cybersecurity teams to embed secure software development practices throughout both traditional and AI-assisted development workflows, including secret scanning, dependency management, vulnerability management, software supply chain security, and secure coding standards.
Partner closely with AI, data, product, cybersecurity, and business leaders to establish engineering standards that enable teams to move quickly while maintaining consistency, security, maintainability, and architectural integrity.
Serve as a hands-on technical leader initially, helping build the foundational tooling, standards, processes, and engineering culture while establishing a longer-term roadmap for the software engineering organization.
Build and develop a high-performing software engineering organization, defining hiring standards, onboarding practices, career paths, engineering expectations, and technical leadership capabilities as the function grows.

Requirements

10+ years of experience in software engineering, including 3-4+ years leading software engineering teams and/or developer platform, Developer Experience, Engineering Effectiveness, or SDLC functions.
Strong foundation as a software engineer, with meaningful hands-on experience building production software and a deep understanding of how software is designed, written, reviewed, tested, deployed, and maintained.
Proven experience leading teams primarily composed of software engineers and building engineering organizations focused on software development, developer tooling, or internal engineering platforms.
Experience building or owning an internal developer platform as a software product, including developer tooling, frameworks, APIs, CLIs, golden paths, self-service capabilities, CI/CD tooling, or IDE integrations.
Deep understanding of the software development lifecycle, including requirements, system design, implementation, code review, automated testing, deployment, production readiness, and maintenance.
Demonstrated success establishing and driving adoption of engineering standards across an organization, including coding practices, code review culture, testing standards, architectural governance, documentation, and software quality.
Strong understanding of Developer Experience and Engineering Effectiveness, including approaches to measuring and improving cycle time, PR quality, test coverage, deployment frequency, DORA metrics, and developer productivity.
Hands-on experience with AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, or similar, with practical knowledge of agentic coding workflows and their application within professional software engineering organizations.
Experience defining standards or governance for AI-assisted software development, including code review, testing, security, documentation, architectural integrity, and production readiness of AI-generated code.
Strong proficiency in modern software development languages and ecosystems, ideally including Python, TypeScript/JavaScript, or similar languages, with the technical depth to engage directly with engineers on architecture, code quality, and tooling decisions.
Experience with modern source control, CI/CD, testing, and software security ecosystems, including GitHub Enterprise, GHAS, SAST/DAST tooling, dependency management, and secure SDLC practices.
Strong leadership, communication, and stakeholder management capabilities, with the ability to influence engineering behavior and drive adoption rather than relying solely on top-down governance.
Ability to operate as both a hands-on technical leader and organizational builder, establishing the foundation today while growing toward broader software engineering ownership over time., * Experience building developer platforms or engineering productivity functions within financial services, fintech, enterprise technology, or other highly regulated environments.
Experience introducing AI-assisted development practices into an established software engineering organization.
Familiarity with emerging agentic development frameworks and standards, including Model Context Protocol (MCP) or similar technologies.
Experience supporting engineering teams working across AI, data, analytics, and enterprise application development.
Familiarity with cloud platforms and modern deployment environments, including Azure, AWS, containers, and Infrastructure as Code, while maintaining a software engineering and developer experience orientation.