Lead Platform Engineer

Accuity

22h•Remote

About The Position

The Lead Platform Engineer is a senior, hands-on technical leader responsible for the direction, reliability, and continued evolution of Accuity's internal engineering platform. The role enables software engineering and data science teams to deploy and operate production workloads in Microsoft Azure through reliable, repeatable, secure, and increasingly self-service capabilities. This position owns the shared infrastructure and delivery pathways that support application teams while preserving clear accountability for application behavior, quality, and production ownership within those teams. The Lead Platform Engineer establishes the platform roadmap, mentors engineers and Software Development Engineers in Test (SDETs), defines technical standards, and contributes directly to high-impact platform design and implementation.

Requirements

7+ years of experience in software, cloud, infrastructure, DevOps, SRE, or platform engineering, including hands-on production systems experience.
Demonstrated experience designing, deploying, and operating workloads in Microsoft Azure.
Experience building reusable platform capabilities, including infrastructure as code, CI/CD, deployment automation, observability, access management, and environment provisioning.
Demonstrated ability to provide technical leadership, mentor engineers, and define clear ownership boundaries across platform, application, and data science teams.
Bachelor’s degree in computer science, software engineering, information systems, or a related technical field preferred.
Equivalent professional experience, technical training, or a combination of education and relevant experience may be considered.
Relevant Microsoft Azure certifications are preferred.
Employees must be able to communicate via phone, email, etc. and sit for extended periods of time, with or without reasonable accommodations.

Nice To Haves

Experience with AI deployment infrastructure, automated testing frameworks, healthcare technology, or regulated environments strongly preferred.

Responsibilities

Define and maintain a focused platform roadmap based on recurring delivery, reliability, and operational challenges experienced by software engineering and data science teams.
Establish technical priorities, engineering standards, architectural direction, and sustainable ownership practices for platform capabilities.
Provide hands-on technical leadership and mentorship to platform engineers, SDETs, and other engineers contributing to platform initiatives.
Evaluate which capabilities should be centralized within the shared platform and which should remain owned by application or data science teams.
Lead technical design discussions, review critical changes, and guide decisions involving platform architecture, reliability, security, scalability, and maintainability.
Promote a pragmatic, service-oriented platform model that creates leverage for engineering teams without introducing unnecessary approval gates or operational dependencies.
Build, maintain, and improve Accuity's Azure-based internal developer platform.
Develop and support infrastructure-as-code solutions for repeatable, secure, and consistent environment provisioning.
Own shared platform capabilities related to configuration, secrets management, cloud identity, network connectivity, CI/CD, deployment automation, and operational tooling.
Design platform services and workflows that reduce manual effort, minimize configuration drift, and improve deployment consistency.
Ensure platform capabilities are resilient, supportable, appropriately governed, and aligned with organizational security and compliance requirements.
Own the lifecycle and consistency of development, test, staging, and production environments.
Manage shared standards and capabilities for provisioning, configuration, access, drift management, deployment promotion, rollback, and environment support.
Create supported, documented, self-service deployment pathways that enable software engineers to release and operate the applications they own with reduced manual platform intervention.
Partner with software engineering teams to improve release reliability while maintaining application-level quality and release accountability within those teams.
Identify recurring delivery activities and convert them into reusable, automated, and maintainable platform capabilities.
Provide and maintain the Microsoft Foundry and Azure infrastructure used to deploy production AI workloads.
Support repeatable provisioning, access controls, network configuration, capacity management, monitoring, promotion, and rollback for AI-related environments.
Partner with Data Science to understand infrastructure and deployment requirements while maintaining clear boundaries between platform responsibilities and ownership of models, evaluations, and data science outcomes.
Help establish secure, scalable, and operationally supportable patterns for deploying AI capabilities in production.
Guide SDETs toward reusable automated validation and test infrastructure that integrates with the shared delivery platform.
Maintain clear ownership boundaries so that application quality and release decisions remain with the appropriate software teams.
Provide shared deployment and operational telemetry that enables teams to monitor the health of their services and troubleshoot production issues.
Diagnose complex platform, infrastructure, deployment, and environment issues.
Improve reliability through automation, standardization, observability, root-cause analysis, and sustainable remediation.
Support incident response and recovery activities for platform-owned systems and shared delivery capabilities.
Create and maintain technical documentation for platform-owned systems, processes, standards, runbooks, and architecture decisions.
Ensure documentation in Confluence and other approved repositories remains current, accurate, accessible, and usable by the broader engineering organization.
Define operational procedures and support models for platform capabilities.
Measure platform adoption, reliability, and business impact using practical indicators such as deployment lead time, change failure rate, recovery time, developer feedback, service adoption, and cloud cost.
Use metrics and stakeholder feedback to prioritize platform improvements and demonstrate measurable value.
Partner with software engineering, data science, quality engineering, security, compliance, and technology leadership to align platform capabilities with business and technical needs.
Communicate platform standards, priorities, architectural decisions, risks, and tradeoffs clearly across a fully remote organization.
Build trusted relationships with engineering teams and use recurring delivery challenges to inform platform priorities.
Support shared planning and decision-making while reinforcing clear accountability across platform, application, and data science teams.
Perform other duties and participate in additional projects as assigned to support departmental and organizational objectives.