Platform Engineering Manager

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Precisely is the leader in data integrity. We empower businesses to make more confident decisions based on trusted data through a unique combination of software, data enrichment products and strategic services. What does this mean to you? For starters, it means joining a company focused on delivering outstanding innovation and support that helps customers increase revenue, lower costs and reduce risk. In fact, Precisely powers better decisions for more than 12,000 global organizations, including 95 of the Fortune 100. Precisely's 2500 employees are unified by four company core values that are central to who we are and how we operate: Openness, Determination, Individuality, and Collaboration. We are committed to career development for our employees and offer opportunities for growth, learning and building community. With a "work from anywhere" culture, we celebrate diversity in a distributed environment with a presence in 30 countries as well as 20 offices in over 5 continents. Learn more about why it's an exciting time to join Precisely!

Precisely is an AI-first organization. All employees are expected to demonstrate proficiency in applying AI tools to accelerate their work, improve output quality, and eliminate low-value tasks. Candidates should be comfortable using generative AI tools (e.g., Microsoft Copilot, ChatGPT) in their day-to-day workflows, able to evaluate AI-generated outputs critically, and open to continuously adopting new AI capabilities as they emerge.

Overview:

We are looking for a Platform Engineering Manager with a strong hands-on engineering background to lead and grow a team of platform engineers focused on developer experience and productivity—enabling engineers to ship high-quality software quickly, safely, and at scale. You will lead by example, champion an AI-forward engineering culture, and mentor your team while contributing to and driving roadmaps for efficient CI/CD pipelines, developer workflows, and AI-powered platform tooling. Rather than owning infrastructure or security directly, your team builds the tooling, guardrails, capacity plans, and right-sized architecture patterns that let engineers move freely without needing deep platform expertise—bringing together capabilities from across platform groups into a single, cohesive experience for developers. You will collaborate across Engineering, Infrastructure, Security, and Product, fostering a culture of end-to-end ownership, fast iteration, and continuous learning.

What you will do:

• Lead a platform engineering team, contributing to and driving roadmaps for efficient CI/CD pipelines, developer workflows, and internal developer tooling.
• Build and curate a "one-stop shop" developer experience by integrating tooling and capabilities from across platform (SRE) groups into a single, self-service interface that gives engineers clear visibility into how their services are performing—including signals like SLO health—so they know when adjustments may be needed.
• Own capacity planning and define right-sized architecture patterns and templates that let engineering teams move and ship confidently without needing the deep platform or infrastructure expertise held by other groups, continuously refining these patterns so that building or scaling a new service gets easier each time.
• Lead development of AI-powered platform tooling, including agent-based workflows that gather context and generate structured, human-reviewed plans for complex platform changes, and automation that streamlines recurring SRE/support workflows (e.g., ticket routing, patching, intake)—getting smarter as more issues are resolved.
• Partner with Engineering, Infrastructure, Security Engineering, and Product—and continuously listen to developer pain points and feedback—to synthesize requirements and prioritize the platform investments with the greatest impact.
• Coach and develop engineers, including technical leads and senior engineers, through frequent feedback and technical guidance, fostering a high-accountability, inclusive culture of end-to-end ownership and fast iteration where failure is treated as a learning opportunity.
• Communicate effectively with technical and non-technical stakeholders, adjusting your approach from strategic framing to technical deep dives as needed.

What we are looking for:

• 1-2 years of experience directly managing software engineers or serving in a technical program management role, including coaching, performance management, and building strong team culture.
• 3-5 years of hands-on software engineering experience (e.g., Go, Python) building developer productivity tools or internal developer platforms, with a strong understanding of the underlying systems, infrastructure, and cloud technologies (e.g., Terraform, Kubernetes, Docker, distributed systems) needed to design effective tooling around them.
• Experience with capacity planning or designing right-sized architecture patterns and templates that let engineering teams self-serve infrastructure decisions without needing deep platform expertise.
• Familiarity with SRE practices, with the ability to translate that knowledge into tooling and automation for support and operational workflows.
• Experience leading teams in a high-velocity, iterative environment, with a bias toward shipping, learning, and continuously raising the engineering quality bar.
• Experience leading or working with globally distributed engineering teams across multiple time zones.
• Strong communication skills and the ability to operate calmly and thoughtfully in complex situations, comfortable balancing technical depth with people leadership.

AI Skills/Knowledge:

• Experience using AI tools for planning and execution—such as roadmap planning, prioritization, and synthesizing requirements or developer feedback into actionable plans.
• Familiarity with AI-assisted coding tools such as GitHub Copilot or Cursor for tasks like PR review, documentation, and technical writing.
• Comfort using AI to support day-to-day management and program management work, including status updates, meeting synthesis, and cross-team communication.
• Familiarity with large language model APIs and agent-based workflows, with sound judgment for evaluating which AI tools and approaches are worth adopting for the team.

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