AI Engineering Manager

We're building an AI-native platform focused on intelligent automation, agentic systems, scalable infrastructure, and high-quality software delivery. We're looking for an Engineering Manager who can lead high-performing engineering teams while staying close to architecture, execution, and customer impact. This is a high-ownership leadership role working directly with founders, product, engineering, and customers to scale a complex AI-driven platform.

Responsibilities:

• Lead and scale a cross-functional engineering team across backend, frontend, AI systems, and platform engineering.
• Drive execution, delivery quality, platform reliability, and engineering velocity.
• Partner closely with Product and GTM teams on roadmap planning and customer escalations.
• Own engineering best practices, sprint execution, code quality, incident management, and production reliability.
• Mentor engineers and help build a strong, high-performance engineering culture.
• Stay involved in technical decision-making, architecture reviews, and system scalability discussions.

Requirements:

• 8-10 years of software engineering experience with 3+ years managing teams.
• Experience leading teams across backend, frontend, and platform systems.
• Strong understanding of distributed systems, cloud infrastructure, APIs, and scalable architectures.
• Proven experience shipping high-quality products in fast-paced environments.
• Strong ownership mindset with experience handling reliability, incidents, and customer-facing escalations.
• Ability to work closely with product and business teams.

Good To Have:

• Experience managing AI/ML or agentic systems teams.
• Background in developer tooling, platform engineering, QA infrastructure, or AI-native products.
• Familiarity with Kubernetes, cloud platforms (AWS/GCP), observability systems, and CI/CD pipelines.
• Experience in high-growth startups or scaling engineering organisations.

Expectations:

• High-quality and predictable engineering delivery.
• Strong platform reliability and operational excellence.
• Faster execution across engineering teams.
• Strong collaboration between engineering, product, and GTM.
• Building a high-performance engineering culture with strong ownership.