Engineering Manager

The Position

You'll build and lead the small founding team — engineers and data scientists — behind something genuinely hard: high-throughput services that inspect live traffic at near-zero latency, and applied ML that runs in the critical path. You're here from person one, which means you don't inherit a culture or a bar — you set them. Who you hire and how they work is the product's first and most important architecture decision.

This is a player-coach role with real surface area. You're close enough to the systems and the models to earn your team's trust, and you own the thing that matters most: whether this team ships, and whether what it ships holds up in production. Small team, huge leverage, nowhere to hide — in the best way.

AI-native leadership. Non-negotiable. You don't just use AI yourself — you build, hire, and coach a team that operates at 10x with it, and you hold that bar. Demonstrable AI proficiency is a hard requirement.

What You'll Own

You own your team's outcomes end to end — what it delivers, how healthy it is in production, and how fast its people grow. You set technical and cultural direction alongside your lead engineers, make the calls that unblock rather than bottleneck, and own the hiring bar from the first req to the tenth. When the path is undefined, you're the one who creates clarity and a plan; when it ships, you're accountable for it behaving exactly as intended, not just passing in staging.

Who You Are

• You lead from the front — hands-on enough that strong engineers respect your judgment, secure enough to let them fully own their work.
• You hire relentlessly and hold a high bar, and you'd rather leave a seat open than fill it with "good enough."
• You grow people — you turn strong individual contributors into force multipliers, and you measure yourself by what your team ships without you in the room.
• You own the result, not the excuse — you take responsibility for delivery and for what runs in production, and you create clarity where there was ambiguity.
• "Good enough" makes you uncomfortable, for the product and for the team you're building.

What You Bring

• Proven, demonstrable AI-native leadership — you personally operate at 10x with AI, and you build, hire, and coach a team that does the same, making AI leverage a standard rather than an experiment.
• 8-10+ years in engineering, including real time leading teams that shipped and operated production systems people depended on.
• Genuine technical depth — you came up through building, and you can still go deep on systems, ML, or both, well enough to guide hard calls and review the work.
• A track record of hiring and growing high-performing engineers and data scientists, and of setting a bar a team is proud to clear.
• The ability to own delivery of an ambiguous, high-stakes charter end to end without trading away quality or the production bar.

Originally posted on Himalayas