Engineering Manager
Pump
Engineering Manager
Pump
AI-driven AWS cloud cost optimization
We're looking for a hands-on Engineering Manager to lead and grow our engineering team as we scale our AI-powered cloud optimization platform. You'll play a key leadership role in shaping technical strategy, building scalable systems, and mentoring top-tier engineering talent.
This is an onsite role where you’ll stay actively involved in architecture and coding, while also managing people and processes. You’ll work closely with the founding team and cross-functional partners to ensure our engineering organization is aligned with product and business goals.
Lead and scale the engineering team from 10 to 20+ engineers, including hiring and team structuring
Stay hands-on with architecture and development—this is a technical leadership role
Own the delivery of scalable, performant systems across AI, infrastructure, and cloud services
Collaborate with product, design, and business teams to translate strategy into execution
Mentor and develop engineers at all levels, fostering a high-performing, inclusive culture
Help shape engineering culture, tooling, and practices as we grow
7+ years of total engineering experience
5+ years in a managerial or technical leadership role
Experience as a CTO, Eng Lead, or similar role at a company with $5M–$30M+ ARR
Strong backend and infrastructure expertise, particularly with AWS, GCP, or Azure
Solid understanding of AI/ML applications in cloud or infrastructure optimization
Degree in Computer Science or a related technical field
Availability to work onsite in San Francisco, Monday–Friday
Previously managed or scaled engineering teams of 10–15+ people
Built and scaled backend systems used by thousands of users
Product-minded and data-driven with strong communication skills
Comfortable navigating ambiguity and moving quickly in a startup environment
Experience in a Series A or growth-stage startup a strong plus
Previous founder or early employee experience is a bonus
Benefits
Pump automates cloud cost savings for AWS by using artificial intelligence to identify and apply optimal optimization strategies without any engineering input from customers. By analyzing usage and automatically applying savings plans, it serves businesses spending roughly $1,000 to $200,000 per month on AWS. Its group billing model pools savings across a growing base and it charges a fee based on the savings achieved. Its goal is to democratize FinOps and make meaningful, hassle-free AWS cost reductions accessible for companies of all sizes.
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