About Kepler

Kepler is building the ground truth platform for AI.

AI is great at understanding what you're asking. It's terrible at giving you answers you can trust. Generic tools hallucinate data, confabulate reports, and provide insights without showing their work. In finance, where being wrong costs millions, that's not acceptable.

We solved this by making accuracy the only possible outcome. Every answer traces to its source. Every calculation is reproducible. Every insight can be defended with complete confidence. The result: faster decisions, deeper analysis, and a competitive edge where synthesizing information more thoroughly than competitors translates directly to performance.

We're starting in finance and building the foundational data layer for anywhere decisions depend on trustworthy data.

Founded by two Palantir veterans with 20 years of combined experience building core parts of Gotham and Foundry. Our founders created Palantir Quiver, the analytics engine behind $100M+ enterprise deals with BP and Airbus, architected core compute and data systems, led major Department of Defense projects, and served as Head of Business Engineering at Citadel.

We're backed by founders of OpenAI, Facebook AI, MotherDuck, dbt, Outerbounds, and others.

The Role

You'll build the agentic infrastructure that powers Kepler's AI research platform. You'll work on the foundational systems that make autonomous AI agents reliable at scale: distributed execution frameworks that run thousands of agents in parallel, evaluation systems that ensure agent quality, context management that maximizes agent performance, and the ontology and provenance systems that let us trace every number back to its source.

This role is for engineers who want to work at the frontier of AI systems, building the infrastructure that makes agents trustworthy for enterprise-critical decisions.

Within your first 90 days, you will:

• Ship your first production agent system with senior mentorship

• Build and deploy infrastructure that powers real financial research workflows

• See your code enable agents to conduct research at top financial institutions

• Take ownership of a core agentic system from architecture to production

What You'll Do

• Build agent execution infrastructure: Distributed systems that orchestrate and run massive numbers of agents in parallel with reliability, retry logic, and graceful degradation.

• Build evaluation systems: Frameworks that measure agent quality, catch regressions, and ensure agents perform reliably across diverse research tasks.

• Optimize agent performance: Context compression, prompt optimization, model routing, and latency reduction. Make agents faster and smarter.

• Build ontology and provenance systems: The semantic layer that maps concepts to precise definitions and traces every output back to authoritative sources. This is what makes our platform trustworthy.

• Integrate AI into production: Language models powering intelligent research workflows with robust error handling, fallback mechanisms, and cost optimization.

• Own systems end-to-end: Design to production. Services, database optimization, deployment, monitoring.

• Ship with production excellence: Comprehensive testing, monitoring, deployment pipelines. You own reliability for what you build.

What We're Looking For

• 7+ years of software engineering experience shipping production systems at scale

• Backend: Python or Node.js, distributed systems, PostgreSQL, Redis, AWS

• Architecture: Experience designing systems that scale and handle complex workflows

• AI/ML systems: Experience building with LLMs, agent frameworks, or ML infrastructure

• Data: Large datasets, ETL pipelines, knowledge graphs or semantic systems a plus

• Practices: Git workflows, CI/CD, automated testing, observability

• Strong communicator who can discuss technical trade-offs clearly

• Curious about the frontier of AI agents and eager to push what's possible

• Thrives in fast-paced environments with high ownership

• Financial services experience preferred but not required

Don't check every box? Apply anyway. We prioritize problem-solving ability, systems thinking, and drive to build transformative agentic infrastructure.

Mentorship & Growth

Direct mentorship from engineers who built Palantir's core systems:

• Weekly 1:1s with senior engineers who've architected enterprise-scale distributed systems

• Deep architectural reviews and guidance on agent system design

• Clear growth path toward technical leadership and system ownership

• Learn by building production agentic systems that power real financial research

Our Technical Stack

• Backend: Python, Node.js, Rust, PostgreSQL, Redis

• AI/ML: OpenAI/Anthropic/OpenRouter Vector Databases

• Infrastructure: AWS, Docker, Temporal, Kubernetes, Kafka, Apache Airflow

• Monitoring: Datadog,

• Tools: Git, GitHub Actions, Pulumi
  

Benefits

• Comprehensive medical, dental, vision, 401k, insurance for employees and dependents

• Automatic coverage for basic life, AD&D, and disability insurance

• Daily lunch in office

• Development environment budget - latest MacBook Pro, multiple monitors, ergonomic setup, and any development tools you need

• Unlimited PTO policy

• "Build anything" budget - dedicated funding for whatever tools, libraries, datasets, or infrastructure you need to solve technical challenges, no questions asked

• Learning budget - attend any conference, course, or program that makes you better at what we're building
  

Our Operating Principles

• Forward-Deployed with Product DNA: We own customer outcomes while building a product company. That means embedding, iterating, and deploying where our customers are. We don't win if they don't win.

• Extreme Ownership: Big vision, shared ownership. If you notice a problem, you own it. Authority comes from initiative, not job titles. Once you step up, you're accountable for the outcome.

• Production-First Engineering: We design for critical workloads from day one. Durable execution, blue/green deploys, automated rollbacks, continuous delivery with end-to-end observability. Every change lands safely and stays resilient under real-world load.

• Trust as the Default: People do their best work when confidence is mutual. We show our work, keep our promises, and flag risks before they bite. Trust isn't an aspiration. It's the baseline.

• Keep Raising the Bar: We block time for training, code-health sprints, and deep-dive tech talks. A sharper team and a cleaner stack pay compounding dividends. Continuous learning isn't a perk. It's part of the job.

Kepler AI is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. We are committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment.