VP of Software Engineering

Job Description

Job Description

The world’s largest organizations rely on Evident to help them protect their business and brand from third-party risk. Our game-changing technology - which enables the secure exchange of risk data like proof of insurance, identity, business registration, and other information - helps our customers verify that their partners have all of the required credentials to do business.

In today’s new remote-first, ever-changing regulatory environment, our secure, privacy-first enterprise platform, accessible via web portal or API, provides a highly scalable and configurable solution to manage communications, storage, decisioning, and ongoing monitoring of credentials.

Evident is a VC-backed technology startup, headquartered in Atlanta, GA. Learn more at evidentid.com.

We’re looking for a VP of Software Engineering to lead and scale our software engineering organization as we build ambitious SaaS products in an AI-first way.

You’ll join an existing engineering team and be responsible for engineering execution, organizational effectiveness, technical direction, and the systems and practices that allow us to build and ship great software at high velocity. You’ll help shape an environment where AI is not treated as a side initiative, but as a natural part of how modern software gets built.

This role is ideal for someone who combines strong technical judgment with the ability to build high-performing teams and leaders. You should be energized by the challenge of scaling both product and organization at the same time: improving execution, raising the bar on engineering quality, and building an operating model that helps the company move faster as technical and product complexity increase.

Key Responsibilities

• Engineering Leadership & Organizational Scale
• Lead and grow the software engineering organization, including hiring, org design, leadership development, and performance management.
• Build a high-accountability, high-trust engineering culture centered on ownership, speed, quality, and customer impact.
• Establish clear operating rhythms, decision-making frameworks, and delivery discipline so teams can execute effectively as the company scales.
• Develop engineering managers and senior technical leaders who can extend your impact across the organization.

• Technical Leadership & Product Delivery
• Own engineering execution across the product and platform, ensuring teams ship high-quality SaaS capabilities with speed, predictability, and strong operational performance.
• Guide architectural decisions and technical strategy across application, platform, data, and integration layers.
• Set and uphold strong engineering standards around code quality, testing, observability, reliability, security, and maintainability.
• Make pragmatic technology and investment choices that balance near-term delivery, long-term scalability, and business impact.

• AI-First Software Development
• Define and lead an AI-first engineering model in which AI is embedded into day-to-day software development workflows across the SDLC.
• Evaluate, implement, and standardize the use of AI tools across the SDLC (e.g., coding assistants, LLM-based code review, test generation, documentation, incident analysis, developer productivity tooling).
• Design workflows where AI is “in the loop” for:
• Requirements refinement and spec drafting
• Architecture exploration and design docs
• Code generation, refactoring, and modernization
• Test case creation and regression detection
• Documentation, runbooks, and onboarding material
• Production troubleshooting and operational analysis
• Establish guidelines, best practices, and guardrails for safe and effective AI use (e.g., security, privacy, IP, data handling, quality standards).
• Measure the impact of AI-enabled workflows and scale the practices that meaningfully improve throughput, quality, and team effectiveness.

• Org & Process Leadership
• Partner with product and company leadership to define how we plan, build, and ship software in an AI-first environment.
• Introduce and refine processes, operating cadences, and tooling that increase throughput, improve predictability, and reduce cycle time.
• Build an engineering organization that can scale without losing quality, urgency, or technical rigor.
• Create mechanisms for experimentation, continuous improvement, and shared learning across engineering.

• Coaching & Mentorship
• Coach engineering managers and senior technical leaders on organizational leadership, execution, and engineering quality.
• Help teams evolve their workflows from basic AI-assisted development to more sophisticated use of AI in complex engineering tasks.
• Provide guidance through architecture reviews, design reviews, operating reviews, and technical decision-making.
• Foster an environment of high standards, strong feedback, and continuous growth.

• Collaboration & Strategy
• Collaborate closely with product, design, and other stakeholders to ensure we’re solving the right problems and investing in the right technical capabilities.
• Help define the roadmap for platform, developer tooling, and engineering investments that unlock greater leverage over time.
• Communicate clearly with leadership about progress, risks, organizational health, and opportunities to increase engineering impact.
• Serve as a strategic partner in company planning, helping align engineering priorities with broader business goals.

Required Skills & Qualifications

• Must have 8+ years of professional software engineering experience, including significant leadership experience in SaaS or cloud software environments.
• Proven experience leading engineering teams and organizations in a scale-up environment, where both product complexity and organizational complexity are increasing.
• A track record of building and shipping sophisticated software products in a modern stack (e.g., cloud-native services, microservices/SaaS, APIs, data-heavy systems, workflow-driven platforms).
• Demonstrated experience leading organizational and technical evolution — e.g., scaling teams, improving engineering execution, platform migrations, process redesign, or adoption of new development practices and tools.
• Hands-on familiarity with AI/LLM tools for software development and strong judgment about where AI materially improves leverage, quality, and speed.
• Strong system design and architectural skills, with the ability to guide scalable, maintainable architectures and communicate trade-offs clearly.
• Excellent communication skills and the ability to lead through growth, complexity, and changing ways of working.
• Strong people leadership skills, including hiring, coaching managers, and developing senior engineering talent.

Preferred Qualifications

• Experience integrating AI- or LLM-based capabilities into production systems or internal engineering workflows.
• Background in developer productivity, platform engineering, or building internal tools and systems for engineers.
• Experience in a high-growth or scale-up environment where speed, ambiguity, and prioritization are central to success.
• Familiarity with data privacy, security, and compliance considerations in the context of SaaS platforms and AI-enabled tooling.
• Experience working on products that involve complex workflows, intelligent automation, data-rich systems, or sophisticated integrations.

Why Evident?

• Our team solves a crucial problem with huge business potential together, and we are able to see exactly how our contribution affects customers!

• Competitive pay package, including base pay and stock options

• Full medical, dental, vision benefits and 401K

• Unlimited PTO

• Paid parental leave to support you and your family

• Home internet stipend, virtual events, & more!

• Recently named one of Atlanta's Coolest Companies & 50 on Fire by Atlanta Inno

• Recently named one of the Top 10 Fastest Growing Companies in Atlanta & one of the Best Places to Work in Atlanta by Atlanta Business Chronicle

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.