About Kepler AI

Kepler AI is building a transparent and intelligent deep-research platform

Financial professionals spend 60-70% of their time manually gathering and consolidating data in a $26.5 trillion industry where speed and accuracy directly impact outcomes. The research landscape has fragmented into dozens of specialized systems — analysts toggle between platforms for financials, transcripts, market data, and macro indicators, reviewing hundreds of documents across disconnected sources for a single investment thesis.
Generic AI tools promise efficiency but fail the trust test. They hallucinate data, confabulate reports, and provide insights without showing their work, forcing analysts back into manual verification. In an industry where being wrong costs millions, opacity isn't acceptable.

Kepler solves this by automating research while maintaining the accuracy and traceability financial decisions demand. The result: faster decisions, deeper analysis, and a competitive advantage where synthesizing information more thoroughly than competitors translates directly to performance.

Kepler AI was founded by two Palantir veterans with 20 years of combined experience building core parts of Palantir's Gotham and Foundry Platform. 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, and Outerbounds.

The Role

As a Software Engineer at Keru, you'll architect and build the intelligent backend infrastructure that powers our autonomous AI research agents. You'll design the core orchestration systems that coordinate multiple specialized AI agents, manage complex multi-step research workflows, and ensure reliable execution of mission-critical financial analysis tasks.

Within your first 90 days, you will:

• Design and ship your first multi-agent workflow system into production with senior mentorship

• Build and deploy an agent orchestration service that handles real financial research tasks

• See your code power autonomous research workflows at top financial institutions

• Take ownership of a core agent system from architecture to production deployment

This role is ideal for engineers who want to build foundational agentic infrastructure at the intersection of AI and finance, where robust system architecture enables autonomous agents to augment human decision-making at enterprise scale.

What You'll Do

• Agent Orchestration & Workflow Engineering: Design and implement sophisticated agent coordination systems that manage complex, multi-step research workflows. Build state machines, task queues, and execution engines that coordinate specialized AI agents across diverse data sources and analysis tasks.

• Multi-Agent System Architecture: Architect scalable systems for agent communication, task delegation, and result synthesis. Implement patterns for agent specialization, load balancing, and dynamic resource allocation across research workflows.

• Autonomous Task Execution: Build robust execution frameworks that handle long-running, multi-phase research tasks with automatic retry logic, error recovery, and graceful degradation. Ensure agents can autonomously navigate complex decision trees while maintaining human oversight capabilities.

• AI Model Integration & Management: Integrate and orchestrate multiple language models (GPT, Claude, specialized financial models) with intelligent routing, fallback mechanisms, and cost optimization. Build abstraction layers that allow seamless model swapping and A/B testing.

• Real-Time Data Pipeline Architecture: Design high-throughput data ingestion systems that process streaming financial data, SEC filings, news feeds, and alternative datasets. Build event-driven architectures that trigger agent workflows based on real-time market events.

• Agent Memory & Context Management: Implement sophisticated memory systems that allow agents to maintain context across long research sessions, learn from past interactions, and build upon previous analysis. Design vector databases and knowledge graphs that support intelligent information retrieval.

• Enterprise Integration & Reliability: Build systems that meet the security and compliance standards of top financial institutions, with comprehensive monitoring, audit logging, and enterprise-grade authentication.

What We're Looking For

Must-haves

• 2+ years of backend systems experience with a proven track record of building production-scale distributed systems

• Strong CS fundamentals: distributed systems, algorithms, system design, and debugging complex multi-service architectures

• Experience with agent frameworks or multi-agent system design patterns

• Expert-level proficiency in Python, Node.js, or Rust with experience in microservices and event-driven architectures

• Hands-on experience with vector databases (Pinecone, Weaviate, Chroma) and semantic search systems

• Track record of shipping: production systems that handle mission-critical workloads and real user traffic

• Clear technical communication: ability to architect complex systems and collaborate with both technical and business stakeholders

Nice-to-haves

• Experience building AI/ML production systems, workflow orchestration, or autonomous agent platforms

• Background with financial data, APIs, or enterprise integration (Bloomberg Terminal, trading systems)

• Knowledge of advanced backend technologies: message brokers (Kafka), container orchestration (Kubernetes), infrastructure as code

• Technical leadership experience: mentoring engineers, making architectural decisions, driving technical strategy

• Startup experience or side projects where you built systems from scratch

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

Mentorship & Growth

You'll be directly mentored by engineers who built Palantir's core systems. Expect:

• 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

At Keru, mentorship accelerates strong systems engineers into exceptional technical leaders.

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. We don't win if our customers don't win. That means embedding, iterating, and deploying where our customers are.

• Extreme Ownership: We have a big vision and everyone owns it. If you notice a problem, you own it - diagnose, coordinate, and close the loop. Authority comes from initiative, not job titles, and once you step up, you're accountable for the outcome.

• Production-First Engineering: We design for customers' most critical workloads from day one. The platform runs on durable execution paths, blue/green deploys, automated rollbacks, and a continuous-delivery pipeline with end-to-end observability, so every change lands safely and stays resilient under real-world load.

• Trust as the Default: We operate on the simple premise that people do their best work when confidence is mutual and earned in the open. That means we show our work, keep our promises, and flag risks before they bite. Automated tests, uptime dashboards, and clear communication back our competence; predictable delivery proves our consistency; candid retros and honest trade-offs reveal our character. Put together, trust isn't an aspiration, it's the baseline everyone can count on.

• Keep Raising the Bar: We block time for training, code-health sprints, and deep-dive tech talks, because 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.