Manage a team responsible for endpoint agent and cloud infrastructure in a fully remote AI observability platform.
Posted by employer 3 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 1 hour ago
What you'll build
Must have
Nice to have
Role intensity
10% coding — mostly leadership/strategy
AI in the day-to-day
Real experience using agentic coding tools, like Claude Code, Codex, or OpenCode.
Requirements
Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
The Technical Engineering Manager at Origin oversees the team responsible for developing the endpoint agent and related services, ensuring that technical priorities are translated into actionable plans. This role requires strong leadership skills, particularly in managing engineers and making informed decisions in a fast-paced AI environment, with a focus on data-intensive systems. Ideal candidates have a background in engineering leadership, particularly in startups, and experience with agentic coding tools. Origin fosters a remote work culture that emphasizes trust, autonomy, and high performance.
Joblaze insights
Quick facts
From the original posting
Our platform monitors and protects some of the most important organizations in the world. We are backed by Sequoia Capital, Brightmind Ventures, IA Ventures and other top VC firms.
Role
Origin is hiring a Technical Engineering Manager to manage the team responsible for our endpoint agent, data and inference services, cloud infrastructure, and customer-facing product. Reporting to the Engineering Lead, you will translate established priorities and technical direction into clear execution plans and keep the team tasked and aligned. You’ll stay close to the work through design reviews, code reviews, production debugging, and hands-on contributions when needed.
The ideal candidate has led high performing teams as a technical or team lead and has managed and developed engineers directly. You bring sound judgment across people, projects, and systems, along with real experience directing agentic coding tools. You’re comfortable working with high agency in a fast-moving, AI-native environment.
Responsibilities
Lead technical execution across the endpoint agent, backend services, inference pipelines, infrastructure, and frontend under the direction set by Engineering leaders.
Translate the priorities and technical direction set by Engineering leaders into clear plans, milestones, and owners.
Turn architecture and design decisions into implementation plans, break complex work into manageable pieces, and help the team make strong day-to-day technical decisions.
Manage, mentor, and develop engineers through clear expectations, regular feedback, coaching, performance management, and career development.
Run a simple, effective cadence for planning, prioritization, progress reviews, and retrospectives.
Hold the team accountable for commitments, quality, and follow-through. Identify delivery or performance issues early and address them directly.
Manage capacity, sequencing, and dependencies. Remove blockers and escalate scope, resourcing, or technical trade-offs when needed.
Take part in hiring and own the successful onboarding of new engineers.
Skills and Experience
5+ years in engineering leadership, including direct people management and experience as a technical or team lead, ideally at a startup.
Strong judgment about when to make a decision, when to raise a trade-off, and when to escalate to Engineering leaders.
A track record building or leading teams that work on data-intensive, high-throughput distributed systems.
Clear communicator who can give direct feedback, align a team, and explain technical trade-offs without overcomplicating them.
Real experience using agentic coding tools, like Claude Code, Codex, or OpenCode, with the judgment to validate their output, redirect them, and know when to take over.
High agency and comfort in an early-stage or fast-scaling environment where priorities shift.
Nice to Haves
Background in observability or real-time monitoring infrastructure, such as Palantir, Datadog, Honeycomb, or Chronosphere
Background in AI infrastructure, particularly inference pipelines, embeddings, or agent orchestration
Experience as the first Engineering Manager, or an early Engineering Lead at a startup
Rust and Python fluency
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