Senior Software Engineer – Agent Systems

kraken.com; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

Kraken is seeking a senior engineer to join a small team building AI-powered agent systems that automate internal workflows and decision paths. The role sits at the intersection of AI, backend engineering, and applied product engineering, balancing rapid prototyping with production-grade reliability.

You will own design and shipping of agents, inference pipelines, and backend services across internal APIs, aiming for scalable, observable, and safe execution.

Qualifications

• 5+ years of producing and shipping production software.
• Strong backend engineering fundamentals across APIs, distributed systems, data modeling, and reliability.
• Comfort working fullstack with backend primary surface and occasional frontend work.
• Hands-on experience with AI/ML systems, large language models, or inference pipelines in production.
• Ability to prototype rapidly while maintaining production-grade architecture.
• Strong systems thinking around orchestration, failure modes, and observability in ambiguous 0→1 settings with high ownership.

Responsibilities

• Design and ship AI-driven agents that automate internal workflows and orchestrate decision paths across company systems.
• Build inference pipelines and backend services that reason over user interactions and internal data sources.
• Prototype agent behaviors quickly, then productionize the ones that prove valuable while maintaining high reliability.
• Define patterns for safe, observable, and controllable agent execution across tools and data sources.
• Identify high-leverage automation opportunities by partnering with product, infrastructure, and internal operations teams.
• Improve system speed, reliability, and signal quality as usage scales.

Skills

Backend engineering

Distributed systems

APIs

Reliability engineering

AI/ML systems

Job description

Role overview

A senior engineering role on a small team building AI-powered agent systems that automate internal workflows and decision paths. The work sits at the intersection of AI, backend engineering, and applied product engineering, balancing rapid prototyping with production-grade reliability. It is a 0→1 environment with high ownership and close collaboration across product, infrastructure, and operations partners.

Responsibilities

• Design and ship AI-driven agents that automate internal workflows and orchestrate decision paths across company systems.
• Build inference pipelines and backend services that reason over user interactions and integrate with multiple internal APIs and data sources.
• Prototype agent behaviors quickly, then productionize the ones that prove valuable while maintaining high reliability.
• Define patterns for safe, observable, and controllable agent execution across tools and data sources.
• Identify high-leverage automation opportunities by partnering with product, infrastructure, and internal operations teams.
• Improve system speed, reliability, and signal quality as usage scales.

Requirements

• 5+ years building and shipping production software systems.
• Strong backend engineering fundamentals across APIs, distributed systems, data modeling, and reliability.
• Comfort working fullstack, with backend as the primary surface and occasional frontend work.
• Hands-on experience with AI/ML systems, large language models, or inference pipelines in production.
• Ability to prototype rapidly while keeping a clear path to production-grade architecture.
• Strong systems thinking around orchestration, failure modes, and observability; comfort operating in ambiguous 0→1 settings 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.
• Background integrating with internal enterprise systems such as CRM, support, or analytics platforms.
• Experience building developer platforms or internal tooling.
• Exposure to designing guardrails, sandboxing, or safety layers for AI systems.

Benefits and work setup

• Applications are accepted on an ongoing basis unless a specific deadline is stated.
• Candidates may redact age, date of birth, or educational dates from resumes.
• Qualified applicants with criminal histories are considered consistent with fair chance hiring practices.
• Hiring is merit-based with an emphasis on diverse backgrounds and perspectives, and applications are encouraged even where requirements are only partially met.