Sr. Engineering Manager

Responsibilities:

• Lead and grow a strong engineering team (6-12+ engineers across levels) building the control plane, edge fleet, and telemetry data path, with focus areas such as fleet reconciliation, telemetry pipelines, edge networking, and Windows collection.
• Own team delivery of backend services, node agents, Kubernetes workloads, and telemetry collectors: planning, prioritisation, and high-quality releases on roadmap commitments.
• Hire, onboard, mentor, run 1:1s, performance discussions, and career development.
• Provide technical guidance (design and code reviews, alignment) on desired- state reconciliation between the cloud control plane and customer-managed fleets, and on delivery reliability (batching, retries, disk buffering, backpressure, failure recovery), while focusing on people leadership.
• Protect the team from distractions; clearly communicate progress and impact to leadership.
• Establish/improve processes for quality, velocity, reliability, and on-call.
• Establish/improve processes for quality, velocity, reliability, on-call, and build, release, and deployment automation; guide diagnosis of issues across cloud services, customer environments, and edge nodes.

Requirements:

• 9+ years of engineering experience + 3+ years of people management (Sr EM: 12+ years total, larger teams/scope), including backend, platform, systems, agent, or data-pipeline engineering.
• Solid technical foundation: experience building or operating production software across distributed environments, with depth in at least one of: Kubernetes operators, controllers, node agents, or cluster management; telemetry/log collection pipelines, observability agents, or streaming systems; Linux networking, proxies, or L4/L7 traffic handling; Windows services, endpoint agents, or Windows event collection.
• Familiarity with service APIs, databases (Postgres), message queues (Kafka), cloud storage (S3, Azure Blob; AWS or GCP), and secret-management services; strong debugging skills across application and infrastructure layers.
• Useful: Kubernetes, k3s, Helm; Vector, Fluent Bit, OpenTelemetry, syslog, NetFlow; disk spooling and at-least-once delivery; nginx stream, PROXY protocol, iptables, conntrack; Windows Event Log, WEC, Winlogbeat; SIEM, security telemetry, or multi-tenant data platforms.
• Proven success scaling teams and products in fast-growth companies.
• Strong coaching, conflict resolution, and culture-building skills.
• Ability to translate technical work into business value; confident presentation.
• Interest in AI-powered data platforms and real enterprise impact.

Skills

AWS, Azure Blob, Fluent Bit, GCP, Helm, K3S, Kafka, Kubernetes, OpenTelemetry, Postgres, S3, Syslog, Vector