Enterprise Platform Engineering Lead

Gray Swan AI; Pittsburgh (Allegheny County); On-site; USD 255,000 - 315,000; Full time

Benefits offered by this job

401k matching

28 days vacation

Health/dental/vision coverage

Catered lunches (Pittsburgh office)

Flexible work arrangements

Visa sponsorship

Job summary

Gray Swan AI is seeking an Engineering Manager, Enterprise to lead a team that builds and scales the systems behind the AI security platform. You’ll own foundational infrastructure, guide cloud strategy, and mentor engineers to deliver reliable, secure services at scale.

You’ll collaborate with ML, security, and product teams to drive architecture decisions and improve developer productivity, all within a fast-moving startup.

Qualifications

• 7+ years of experience building enterprise solutions.
• 2+ years of experience managing, mentoring, or leading software engineering teams.
• Strong technical background in infrastructure, distributed systems, backend engineering, or platform engineering.
• Strong programming experience in C/C++, Go, Python, Rust, Java, or a similar language.
• Experience operating production services on Kubernetes and modern cloud platforms such as AWS, GCP, and Azure.
• Deep understanding of networking, distributed systems, containers, service orchestration, and scalable architectures.
• Experience designing and operating APIs, microservices, asynchronous systems, and event-driven architectures.
• Strong understanding of reliability, observability, security, and performance at scale.
• Comfortable diving into complex technical problems and debugging production systems alongside your team.
• A strong people leader who enjoys coaching engineers, providing feedback, and helping individuals grow.
• Able to balance technical depth with effective delegation and team leadership.
• Excited to work in a fast-moving startup where you will have significant ownership and ambiguity.

Responsibilities

• Lead, mentor, and develop a team of infrastructure engineers, creating a culture of ownership, technical excellence, and continuous improvement.
• Set technical direction and priorities for enterprise solutions in partnership with engineering leadership and other technical teams.
• Oversee the design, development, and operation of highly available backend services and distributed systems that power Gray Swan’s AI security platform.
• Guide the team in owning and scaling cloud infrastructure across Kubernetes, AWS, GCP, Azure, networking, storage, and compute.
• Drive the development of internal platform services, infrastructure tooling, and systems that improve developer productivity and reliability.
• Establish and improve engineering practices around observability, monitoring, incident response, deployment, and operational excellence.
• Partner closely with machine learning, security, and product engineering teams to build infrastructure capable of supporting increasingly complex AI workloads.
• Identify and address opportunities to improve system performance, reliability, scalability, and infrastructure efficiency.
• Help define long-term architecture and technical strategy while balancing immediate product and engineering priorities.
• Participate in hiring and help build a world-class infrastructure engineering organization.
• Provide technical guidance during complex production incidents and ensure the team learns from failures through effective post-incident reviews.
• Communicate infrastructure strategy, tradeoffs, risks, and priorities clearly across engineering and company leadership.

Skills

Leadership

Infrastructure engineering

Distributed systems

Backend architecture

Cloud platforms

Observability

Site reliability

Tools

Kubernetes

AWS

GCP

Azure

Terraform

PostgreSQL

Redis

Kafka

Job description

Gray Swan AI is seeking an Engineering Manager, Enterprise to lead a team that builds and scales the systems behind the AI security platform. You’ll own foundational infrastructure, guide cloud strategy, and mentor engineers to deliver reliable, secure services at scale.

You’ll collaborate with ML, security, and product teams to drive architecture decisions and improve developer productivity, all within a fast-moving startup.