Head of Internal Tools Engineering, Artificial Intelligence (AI) Required, Work From Home
$170k - $225kNext Step Systems
Job Description Head of Internal Tools Engineering, Artificial Intelligence (AI) Required, Work From Home We are seeking a Head of Internal Tools Engineering candidate for a great work from home opportunity. You will architect, build, and scale the internal technology ecosystem that accelerates workforce productivity, eliminates operational friction, and gives the company a compounding infrastructure advantage. You will treat internal tools with the same product rigor and user-centricity as any external product because the quality of internal systems directly determines organizational velocity. You will lead a cross-functional engineering team, make high-stakes build-vs-buy decisions, and drive AI adoption into internal workflows. This role requires someone who can see the company’s operational architecture as a system design problem and solve it with software. This position is 100% Remote. Head of Internal Tools Engineering Responsibilities: Internal Platform Strategy & Roadmap:
- Own the end-to-end strategy and roadmap for all internal tools, platforms, and automation treating internal technology as a product, not a cost center.
- Make strategic build-vs-buy decisions, knowing when a custom-built solution creates a lasting advantage and when a SaaS tool is the right answer.
- Map current and next-state process flows across the entire internal toolchain and lead systems transformation for internal teams.
- Architect and maintain the full engineering lifecycle for internal platforms from ideation and design through deployment, iteration, and deprecation.
- Build seamless, API-first ecosystems that integrate internal tools across HR systems, finance platforms, knowledge management, CRM, and developer infrastructure.
- Own system reliability and operational resilience: establish success metrics for uptime, performance, and employee productivity.
- Design scalable, secure architectures using cloud-native principles, microservices, and modern integration patterns.
- Lead the strategy for integrating AI and LLMs into internal workflows reimagining how knowledge is shared, decisions are supported, and work is executed across the organization.
- Deploy intelligent automation tools including AI where appropriate to streamline internal processes and improve decision-making.
- Evaluate and integrate AI-assisted troubleshooting, proactive recommendations, and intelligent automation into the internal platform layer.
- Stay ahead of technology trends and drive continuous experimentation you build prototypes, not slide decks.
- Reduce cognitive load for internal users by providing golden paths, standardized workflows, and self-service capabilities.
- Ensure frictionless onboarding and seamless integration across the tool ecosystem.
- Measure platform success through adoption rates, user satisfaction, DORA metrics, and productivity impact not feature count.
- Build, lead, and mentor a high-performing team of engineers and engineering managers.
- Cultivate a collaborative engineering culture rooted in ownership, speed, and craftsmanship.
- Provide technical mentorship and create growth paths for individual contributors and managers alike.
- Foster psychological safety and a feedback-driven environment that empowers people to do their best work.
- Partner with People, Finance, Engineering, Legal, and Operations leadership to translate complex business needs into a unified technical vision.
- Serve as the bridge between business stakeholders and the engineering team you speak both languages fluently.
- Align internal platform investments with broader company strategy and demonstrate measurable ROI.
- 12+ years of experience in software engineering, with at least 5 years in engineering leadership (managing teams or managing managers).
- Artificial Intelligence (AI) experience required.
- Strong hands-on technical background; you’ve built production systems and can still credibly review architecture, code, and system design.
- Deep understanding of cloud-based systems (AWS, GCP, or Azure), APIs, microservices, data pipelines, and modern infrastructure.
- Proven track record of building and scaling internal tools or platforms that serve cross-functional business teams not just engineering.
- Experience making build-vs-buy decisions and managing a portfolio of custom-built and third-party tools.
- Strong experience designing and building internal platforms and automation systems.
- Strong product thinking: you define success in terms of user outcomes and business impact, not technical output.
- Experience navigating the full SDLC from ideation through deprecation you know when to build, iterate, and retire.
- Excellent communication skills: you can articulate complex technical concepts to non-technical executives and translate business problems into engineering roadmaps.
- Experience at a high-growth technology or AI-native company that scaled rapidly is a plus.
- Background in platform engineering, developer experience, or internal developer platforms (IDPs) is a plus.
- Familiarity with HRIS, ERP, and business systems integration (Workday, Salesforce, NetSuite, etc.) is a plus.
- Experience with cybersecurity best practices and compliance frameworks for internal systems is a plus.
- Prior experience leading internal technology through M&A integrations or multi-entity consolidation is a plus.
- Exposure to knowledge management systems, internal search, and enterprise AI assistants is a plus.
- Experience integrating AI/LLMs into internal workflows or productivity tools is a plus.
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