Agentic Systems Engineer
Build agentic infrastructure for reliable AI agents including distributed execution frameworks, evaluation systems, context management, and provenance layers for enterprise-critical decisions.
About the job
What You'll Own
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
Our Technical Stack
- Backend: Rust - agent orchestration, data extraction, computation pipelines
- Frontend: TypeScript, React - the analyst workspace and verification interfaces
- Data: PostgreSQL, plus direct integrations with official data sources
- Infra: AWS
- AI: Model-agnostic by design. We currently use Claude and GPT. The model is the replaceable part.
Skills
Python, Node.js, Rust, Distributed Systems, Postgres, Redis, AWS, LLMs, Agent Frameworks, TypeScript, React
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