
Senior Software Engineer
Posted Sep 17

Posted Sep 17
This is a fully remote position, open to applicants in California.
β’ Take ownership of the entire lifecycle of LLM-powered functionalities, from prototype development and prompt design to production rollout, monitoring, and iterative improvements.
β’ Create fine-tuning workflows, evaluation harnesses, and inference infrastructure that serve users at scale.
β’ Design and implement autonomous agent architectures that include orchestration layers, memory systems, guardrails, and feedback loops.
β’ Define agent behaviors, constraints, and failure modes to guarantee safe, explainable, and smooth operation.
β’ Design, develop, test, and deploy code for intricate functional areas.
β’ Architect and implement modern services that are scalable, highly available, and fault-tolerant.
β’ Construct backend services and APIs that facilitate secure interactions between AI agents and both internal and external systems.
β’ Utilize AI-assisted development tools and contribute to the establishment of team-wide agentic authoring practices.
β’ Work collaboratively with product management, solution architects, AI/ML practitioners, and cross-functional teams.
β’ Convert ambiguous business challenges into clearly defined, outcome-oriented solutions.
β’ Implement secure, observable, and production-ready solutions.
β’ Develop evaluation strategies, monitor costs, set latency budgets, and establish guardrails.
β’ Engage in design, code, artifact, and metrics reviews.
β’ Provide consistent feedback, mentor colleagues, and promote continuous improvement.
β’ Champion modern engineering practices that enhance velocity, robustness, and quality.
β’ Over 5 years of experience as a software engineer developing production-grade systems.
β’ Proven experience in transitioning LLM-powered features from prototype to production, including prompt engineering, evaluation, deployment, and iteration.
β’ Practical experience in building agentic systems, encompassing planning/reasoning loops, tool usage, memory/context management, and orchestration.
β’ Strong background in constructing large-scale backend services and APIs utilizing modern languages and frameworks.
β’ Experience with AI-assisted development tools like Cursor, Claude Code, or GitHub Copilot.
β’ Solid grasp of LLM operational aspects, including token economics, latency optimization, model routing, caching strategies, and cost management at scale.
β’ Experience in designing evaluation frameworks and quality metrics for AI systems.
β’ Strong knowledge of software engineering principles, cloud-native infrastructure, and distributed system architecture.
β’ Capability to build robust, scalable, and reusable solutions that safely incorporate AI functionalities into core platforms.
β’ Ability to mentor and influence fellow engineers.
β’ Proficient in self-unblocking and assisting the team in achieving complex, cross-disciplinary objectives.
β’ Outcome-focused mindset, utilizing metrics and data to assess system performance and development efficiency.
β’ Experience promoting engineering best practices through tools and automation.
β’ Familiarity with deployment and observability strategies that support continuous delivery and high availability.
β’ Medical insurance
β’ Dental insurance
β’ Vision insurance
β’ 401k
β’ PTO/paid sick leave
β’ Employee stock purchase plan
β’ Inclusive workplace culture
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