Kepler  Logo

Kepler

Forward Deployed Engineer

Reposted 11 Days Ago
In-Office
New York City, NY
200K-280K Annually
Mid level
In-Office
New York City, NY
200K-280K Annually
Mid level
As a Forward Deployed Engineer, you'll customize and optimize AI solutions at client sites, engaging directly with financial firms to drive product innovation and improve research workflows.
The summary above was generated by AI
Introducing KeplerThe Problem

High-stakes industries are falling behind on AI adoption. Their workflows can’t afford wrong answers. And AI can’t be trusted to give right ones because of hallucinations. The barrier isn’t that the models aren’t smart enough. It’s that no one can verify what they produce. The fix isn’t a better model, it’s a trust layer: every output traceable, every calculation auditable, every answer reproducible.

What Kepler Is

Kepler is the agent harness - the infrastructure layer that wraps around AI models to make their outputs reliable, traceable, and verifiable. The model is a replaceable component. The harness is the product.

In Kepler's architecture, the LLM orchestrates - it decides what data to gather, what to compute, how to structure the output. But every actual data point, every extracted value, every calculation flows through deterministic code pipelines. The LLM never touches the data itself. Every value carries provenance metadata back to its exact source. Every computation is auditable and reproducible. Verification loops cross-check outputs before users ever see them.

We started in finance because the stakes are highest and the tolerance for error is zero. We’ve built a finance research product that lets analysts supercharge their workflow: pulling comparables, building models and researching filings. No more double-checking every number AI spits out. Every number tracing back to the source, every time.

But the architecture - provenance, deterministic computation, verification - applies anywhere trust in AI output matters: chemicals, legal, healthcare. Models are commoditizing fast. The trust layer is what's missing and the market is massive.

The Team

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.

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 RoleWhat You'll Own

As a Forward Deployed Engineer at Kepler, you'll be the technical architect of our most strategic client relationships. You'll work directly on-site with our lighthouse customers, sophisticated financial firms and research organizations. to deploy, customize, and optimize Kepler's AI-native research platform for their specific workflows and requirements.

This is the engineering role that lives our core principle: "Forward-Deployed with Product DNA." You'll embed directly with clients to own their outcomes while simultaneously building the platform that serves the entire market. Your code decisions can impact million-dollar research outcomes.

Within your first 90 days, you will:

  • Rapidly build and develop vertical apps on top of our core platform.

  • Engage with Portfolio Managers at institutions with 10B+ AUM to scope and build workflows.

  • Develop deep expertise in agentic tooling, products, and technologies.

  • Own a customer engagement end-to-end.

This is the right role if you want to build the future of financial research while working directly with the world's most sophisticated analysts with guidance from engineers who've scaled enterprise platforms from zero to global adoption.

What You'll Do
  • Engineer solutions at client sites: Deploy and customize AI research workflows directly where critical financial decisions happen, rapidly prototyping solutions that push our platform's boundaries.

  • Drive product innovation from the field: Identify technical gaps while embedded with clients, then architect and implement new capabilities that become core product features.

  • Build enterprise integrations: Design complex integrations with client data infrastructure, research tools (Bloomberg, CapIQ), and proprietary trading systems.

  • Optimize platform performance: Scale our AI platform for client-specific use cases, solving complex performance challenges in real-world research environments.

  • Bridge field and product: Rotate between forward deployed work and core platform development, bringing field insights directly into our technical architecture.

  • Own critical deployments: Ensure our platform performs reliably for clients' most critical research operations, debugging issues across the full stack.

What We're Looking For

Must-haves

  • 5+ years building production software, with a track record of deploying complex systems in enterprise environments. No upper limit, comp scales with experience.

  • Client-facing technical experience: Previous role as Forward Deployed Engineer, Solutions Engineer, or similar position working directly with enterprise customers.

  • Full-stack development skills: Strong capabilities in Python/TypeScript with experience in distributed systems, data pipelines, and API development.

  • Enterprise integration / data integration expertise: Experience with SSO/SCIM, RBAC, database integrations, and enterprise security requirements.

  • Communication and presentation skills: Comfortable presenting to C-level executives and technical teams alike.

  • Travel flexibility: Willingness to travel regularly (30-50%) for on-site client engagements from our NYC HQ.

Nice-to-haves

  • Financial services exposure: Previous experience working with financial firms or familiarity with research workflows.

  • Data platform experience: Background with large-scale data processing, ETL pipelines, or analytics platforms.

  • Rust development experience.

  • Startup experience where you owned features end-to-end.

Don't check every box? Apply anyway. We prioritize speed of learning, problem-solving skills, client empathy, and drive to transform how financial research works.

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 Kepler, 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

Working at KeplerOur 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.

  • Daily lunch in office.

  • Unlimited PTO policy.

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

  • "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
  • 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.

  • Forward-Deployed with Product DNA: We own customer outcomes while building a product company. We don't win if they don't win.

  • Extreme Ownership: If you notice a problem, you own it by by making sure it doesn’t fall through the cracks. 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.

  • Communicate with Intent: Great work disappears without great communication. We push information to the people who need it, when they need it. Silence is never the safe choice.

  • Earn it Every Day: Your work speaks for itself. We create an environment where the best idea wins, the strongest work gets recognized, and everyone is held to the same high standard.

  • Keep Raising the Bar: 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. 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.

Similar Jobs at Kepler

3 Days Ago
In-Office
200K-280K Annually
Senior level
200K-280K Annually
Senior level
Fintech • Software
Build and own Kepler's cloud and infra foundation: AWS account architecture, IaC, deployment pipelines, enterprise in‑VPC deployments, security/SOC2 controls, developer platform tooling, database scaling, and production reliability (SLOs, on‑call, incident response).
Top Skills: AWSAws CdkCi/CdClaudeEcsEksGptIamKmsObservabilityPostgresPulumiPythonRdsReactRustSAMLScimSecrets ManagementSoc 2SsoTerraformTypescriptVpc
11 Days Ago
In-Office
250K-350K Annually
Senior level
250K-350K Annually
Senior level
Fintech • Software
Develop foundational systems for Kepler's AI platform, including building execution infrastructure, evaluation systems, and integrating AI into production environments. The role requires strong backend engineering skills and experience in AI/ML systems.
Top Skills: AnthropicAWSDockerKubernetesMcp SdkNode.jsOpenaiPostgresPythonReactRedisRustTypescript
11 Days Ago
In-Office
200K-280K Annually
Mid level
200K-280K Annually
Mid level
Fintech • Software
As a Software Engineer at Kepler, you'll develop backend systems, manage data pipelines, and integrate AI for financial applications, ensuring production excellence and scalability.
Top Skills: AWSDataflowDockerGitGitKubernetesNode.jsOpenaiPostgresPythonReactRustTypescript

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account