Kepler
Platform Engineer
New York City
Sponsorship not specifiedDetected 47 days ago
TypeScriptPythonRustReactPostgreSQLAWSTerraformCI/CDPlatform EngineeringdbtNLPLLMsAI OrchestrationCybersecurityIncident ResponseComplianceProcurementResearchLeadershipProblem SolvingMentoring
About the role
- Stand up the enterprise deployment model (single-tenant, in-VPC, BYOK).
- Set the security baseline (SOC 2 controls, audit logging, identity, network isolation) that converts procurement reviews into closed deals.
Responsibilities
- Build systems that earn trust under real load.
- You'll tell someone their design has a flaw before the PR goes in, not after.
- "Build anything" budget - dedicated funding for whatever tools, libraries, datasets, or infrastructure you need to solve technical challenges, no questions asked.
- Forward-Deployed with Product DNA: We own customer outcomes while building a product company.
- Extreme Ownership: If you notice a problem, you own it by by making sure it doesn't fall through the cracks.
- Production-First Engineering: We design for critical workloads from day one.
- We create an environment where the best idea wins, the strongest work gets recognized, and everyone is held to the same high standard.
Requirements
- You don't need to be the team's strongest Rust dev, but you can read and contribute to it.
- You know what it feels like when the plan changes twice in a day and the work still has to ship.
Nice to have
- We're backed by investors who built the modern AI and data stacks, plus the builders of iconic commercial businesses.
- This includes founders of OpenAI, Meta AI Research, MotherDuck, dbt Labs and Square as well as PebbleBed, Company Ventures and Mantis VC firms.
- The cloud, databases, deployment fabric, and security posture that financial institutions stake their workflows on.
- This is the first dedicated platform hire.
- You're defining how Kepler ships, scales, and earns trust from the most security-conscious buyers in the world.
- This isn't a service role.
- It's the role that defines how Kepler ships.
- You've owned the AWS account, the IaC repo, and the pager.
Skills
- Cursor, Claude Code, whatever makes us faster.
- Our users are analysts at firms where a wrong number costs real money.
- The pace is startup-fast but the engineering bar is high.
- Fluency is assumed.
- Great teams compound.
- Every hire raises the bar, every win gets named, every person gets the tools and runway to grow.
- Kepler is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.
Benefits
- 100% covered top-of-the-line medical, dental, and vision insurance for employees and their families.
- HSA maxed by the company to the IRS limit.
- Automatic coverage for life, AD&D, and disability insurance.
- Unlimited PTO policy.
- Learning budget - attend any conference, course, or program that makes you better at what we're building.
Company info
- The founding team spent a combined 40+ years at Palantir building the type of large-scale data infrastructure that Kepler requires.
- Our CTO created Palantir's first AI platform and built the analytics engine behind $100M+ contracts.
- Our founding engineers led Foundry's core systems - Ontology, Fusion, Workshop, FoundryML - and scaled data products at Meta to 1B+ users.
- We've paired this deep technical foundation with a repeat founder profile.
- Our CEO built and scaled a data company to $15M ARR before successfully selling it.
- He then became Citadel's first Head of Business Engineering, experiencing first hand the problems we are now solving.
- We have a team who've been on both sides: building systems like this at massive scale and selling it into the buyers who need it most.
- You'll own the infrastructure foundation of Kepler's AI research platform.
- Every model invocation, every analyst query, every enterprise deployment runs on what you build.
Equal opportunity
- Equal Opportunity Employer and prohibits discrimination and harassment of any kind.
This listing is sourced directly from Kepler's careers page and normalized into a canonical job model.