Senior Software Engineer

This is a fully remote position, open to applicants in Arizona, +13 more states.

📋 Description

• Design, develop, manage, and maintain production SaaS features that incorporate RAG pipelines, agent systems—including multi-agent architectures—and deterministic services.

• Utilize AI coding agents (e.g., Claude Code style tools) as an integral part of your development workflow, covering architecture exploration, implementation, testing, refactoring, and documentation, while ensuring complete ownership of output quality and comprehending their strengths and limitations.

• Implement and enhance agentic systems using frameworks like LangChain, CrewAI, PydanticAI, or similar, focusing on tool orchestration, memory/state management, and multi-step reasoning workflows.

• Construct scalable retrieval and inference pipelines: embedding workflows, vector databases, hybrid retrieval strategies, caching, and evaluation loops to optimize accuracy, latency, and cost.

• Determine where agentic methods offer advantages over traditional coding and where they don't, making practical, production-oriented trade-offs regarding cost, accuracy, latency, and reliability.

• Develop guardrails and failure-mode mitigations for non-deterministic systems, encompassing prompt structuring, validation layers, fallback strategies, and human-in-the-loop patterns as needed.

• Incorporate observability and evaluation into AI-powered features, tracking correctness, drift, bias, and performance over time.

• Collaborate with architects, product managers, and designers to convert ambiguous requirements into solid technical designs.

• Contribute to shared libraries, internal tools, and reference patterns that expedite the delivery of AI-driven features across various teams.

• Engage in code reviews and design discussions, raising standards for quality, reliability, and responsible AI usage within the engineering organization.

• Mentor fellow engineers on effective agentic coding practices, prompt design, and emerging trends as adoption expands.

• Take ownership of AI-enabled features from start to finish in production, covering initial design and implementation through to deployment, monitoring, on-call support, incident response, and iterative enhancement.

⛳️ Requirements

• Over 7 years of professional software engineering experience, with a robust background in building and managing SaaS platforms in production.

• Demonstrated experience working at a SaaS organization, contributing to multi-tenant, cloud-based systems.

• Practical experience designing or significantly contributing to SaaS platform architecture, including clearly defined service boundaries, API design, domain modeling (DDD), data modeling, and integrations across distributed systems.

• Advanced, hands-on experience with AI coding agents in daily development, encompassing real production work with clear accountability for outcomes.

• Strong experience with agentic systems and AI workflows, including RAG architectures and retrieval pipelines, LLM integrations, prompt engineering, context engineering, agent orchestration, tool-chaining, and evaluation and observability for AI outputs.

• Familiarity with agentic frameworks such as LangChain, CrewAI, PydanticAI, or similar, along with the discernment to know when to extend, replace, or simplify them.

• Comprehensive understanding of software engineering principles, including SOLID principles, clean architectural layering, widely-used design patterns, testing strategies, and performance optimization.

• Experience in building and managing production systems with strong engineering discipline, encompassing testable system design, observability, progressive delivery, and reliability patterns that minimize blast radius and enable safe iteration.

• Comfort in operating within cloud-native environments (AWS, Azure, or GCP), including microservices, event-driven architectures, CI/CD, and production monitoring.

• Experience in designing secure, multi-tenant SaaS systems, including access control patterns, data isolation, and defensive design practices suitable for AI-enabled applications.

• Strong communication abilities, capable of clearly explaining complex technical and AI-driven behaviors to engineers, product partners, and stakeholders, as well as mentoring other engineers through code reviews, design discussions, and thoughtful technical guidance.

• A commitment to continuous learning, experimentation, and responsible innovation, especially as agentic capabilities rapidly evolve.

• Although a Bachelor’s degree is preferred, we place greater importance on demonstrated experience and impact.

🏝️ Benefits

• Medical, vision, dental, and life insurance, along with short- and long-term disability coverage.

• Generous paid time off (PTO) that increases with your tenure at Ozmo, in addition to paid holidays.

• 401k retirement savings plan with employer matching.

• Paid maternity and bonding leave for new parents.

• Paid pawternity leave when you welcome a new pet into your home.

• A one-month sabbatical after five years of service with Ozmo.

• Flexible remote work arrangements to support your optimal performance.