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Senior Software Engineer – Agent Systems

Kraken Digital Asset Exchange United States ; United States (whole country)
Full-time Remote work

Publication date: 02/11/2026

The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration. This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving: prototypes are expected, but the bar for production reliability remains high.

Responsibilities

Build and ship AI-powered agent systems that automate internal workflows and decision paths; Design and implement inference pipelines that reason over user interactions across internal systems; Prototype quickly to validate agent behaviors, then productionize what proves valuable; Architect backend services that integrate with multiple internal APIs and data sources; Define patterns for safe, observable, and controllable agent execution; Collaborate cross-functionally to identify high-leverage automation opportunities; Improve system speed, reliability, and signal quality as usage scales; Contribute to foundational design decisions for a 0→1 agent platform

Requirements

5+ years of experience building and shipping production software systems; Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability); Experience building fullstack systems, with comfort working across backend and occasional frontend surfaces; Hands-on experience working with AI/ML systems, LLMs, or inference pipelines in production; Ability to prototype rapidly while maintaining a clear path to production-grade architecture; Strong systems thinking, able to reason about orchestration, failure modes, and observability; Comfort operating in ambiguous, 0→1 environments with high ownership

Nice to have

Experience building or operating agent-based systems or autonomous workflows; Familiarity with prompt engineering, evaluation frameworks, or model performance tuning; Experience integrating with internal enterprise systems (CRM, support tools, analytics platforms, etc.); Background in building developer platforms or internal tooling; Experience designing guardrails, sandboxing, or safety layers for AI systems
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