VP of Software Engineering - Platform
- Firstup
- Remote USA
Job Description
We are seeking a VP of Software Engineering, Platform to lead one of the company’s most strategic engineering functions: the platforms that enable our product teams to build faster, integrate more deeply, operate more reliably, and deliver AI-native enterprise software at scale.
This leader will own the strategy and execution for our application development platform, agentic AI platform, integration platform, data platform, reporting and analytics capabilities, and AI-native software development lifecycle.
The ideal candidate is a hands-on technical executive who can set long-term strategy, lead multiple teams, develop senior technical talent, and engage deeply in architecture across cloud-native systems, AI platforms, data infrastructure, and enterprise integrations.
What You'll Do
Define and Execute Platform Strategy
● Lead the platform engineering vision, roadmap, operating model, and execution plan.
● Build a cohesive organization across shared services, AI platform, integrations, data engineering, reporting, analytics, and developer experience.
● Translate business and product strategy into platform capabilities that improve speed, reliability, security, scalability, and customer value.
● Establish ownership models, platform adoption strategies, service maturity standards, and measurable outcomes
Build Enterprise-Grade Application Platforms
● Own foundational services including API Gateway, Developer Portal, Authentication, Authorization, Logging, Audit Trail, service templates, and platform libraries.
● Drive a paved-road development model that improves velocity while preserving appropriate team autonomy.
● Ensure shared services are reliable, observable, secure, well-documented, and easy to adopt.
● Provide technical leadership across AWS, Kubernetes, Ruby on Rails, Node, Python, PostgreSQL, and related cloud-native technologies.
Lead the Agentic AI Platform
● Own the strategy, architecture, and execution for the company’s agentic AI platform.
● Build reusable capabilities for tool definition, retrieval and grounding, model interaction, permission context, tracing, evaluation, versioning, and usage reporting.
● Enable teams to develop AI-powered features safely and quickly using OpenAI SDK, MCP, Python, Node, and related technologies.
● Establish patterns for permission-aware agents, grounded responses, tool execution, model orchestration, evaluations, and production observability.
Transform Software Development with AI
● Lead the company’s AI-native software development lifecycle strategy.
● Standardize agent skills, plug-ins, local development environments, templates, and workflows.
● Enable AI-assisted development across coding, testing, code review, documentation, release management, support, and operations.
● Define guardrails for security, code quality, data privacy, intellectual property, and responsible AI usage.
Own Enterprise Integrations
● Define the technical strategy for enterprise integrations and ecosystem connectivity.
● Lead integration capabilities using APIs, MCP, agents, and scalable integration patterns.
● Own integrations with HRIS, ITSM, Microsoft SharePoint, Microsoft Teams, and other enterprise operational systems.
● Reduce integration complexity through reusable connectors, authentication patterns, monitoring, documentation, and supportability standards.
Lead Data Platform, Reporting & Analytics
● Own data engineering, customer-facing reporting, internal analytics infrastructure, and analytics products.
● Build scalable data pipelines, data models, warehouse architecture, reporting infrastructure, and analytics enablement.
● Provide leadership across PostgreSQL, Redshift, AWS data services, and related data technologies.
● Drive data quality, lineage, governance, privacy, access control, and reliability.
Build and Lead the Organization
● Lead multiple teams across platform engineering, AI platform, integrations, data engineering, analytics, and developer experience.
● Hire, mentor, and develop managers, architects, staff engineers, and senior engineers.
● Create clear goals, ownership, operating rhythms, and accountability across the organization.
● Build strong partnerships with Product, CloudOps, Security, Customer Success, Implementation, Data, and executive leadership.
What We're Looking For
Executive Engineering Leadership
● 15+ years of software engineering experience, with significant leadership experience in enterprise SaaS, platform engineering, data platforms, integrations, infrastructure, or AI-enabled product development.
● 5+ years leading engineering organizations at senior director, VP, or equivalent levels.
● Proven ability to translate business and product strategy into technical strategy, operating plans, and measurable outcomes.
● Experience leading multiple teams, managers, senior technical leaders, and complex cross-functional initiatives.
Technical Judgment
● Experience building shared platform services, internal developer tooling, integration platforms, data platforms, and AI platform capabilities.
● Hands-on experience with AWS, Kubernetes, Ruby on Rails, Node, Python, PostgreSQL, Redshift, OpenAI SDK, MCP, and related technologies.
● Ability to engage deeply in architecture reviews, technical tradeoffs, implementation approaches, and operational risk decisions.
Strategic Platform Mindset
● Ability to identify repeated engineering needs and convert them into reusable, scalable, well-adopted platform capabilities.
● Strong product mindset for internal platforms, with focus on adoption, usability, documentation, developer experience, and measurable impact.
● Strong judgment on when to standardize, when to allow flexibility, when to build, and when to buy.
Leadership & Mindset
● Hands-on technical executive who earns trust through depth, clarity, and follow-through.
● Pragmatic, collaborative leader who can operate in ambiguity and create alignment.
● Strong communicator across engineers, executives, customers, and cross-functional stakeholders.
● Passion for building high-performance teams, developing leaders, and creating a durable engineering culture.
● Bias toward outcomes, leverage, simplicity, customer impact, and continuous improvement.
