Senior Software Engineer

Ozmo is seeking a Senior Software Engineer to build and ship AI-first software that delivers real, automated outcomes  this role, you'll be hands‑on designing and implementing production systems that combine traditional software engineering with modern agentic workflows, including AI coding agents, and multi‑agent orchestration frameworks.

You'll collaborate with product, architecture, and engineering teams to design and ship scalable SaaS features that integrate generative AI capabilities into production systems. This role is intended for engineers who actively use AI coding agents in their day‑to‑day work and are comfortable designing systems that account for non deterministic behavior, while understanding the strengths and limitations of current AI tools.

As a growing technology company, Ozmo is transforming how enterprises leverage AI to deliver automated outcomes 're building a team of engineers who thrive on solving hard problems, shipping production systems that matter, and thoughtfully integrating AI into enterprise‑grade SaaS solutions. If you're excited about building agentic systems that actually work in production and helping define best practices along the way, this role is for you.

• Design, build, own and operate production SaaS features that integrate RAG pipelines, agent systems including multi‑agent architectures, and deterministic services.
• Use AI coding agents (e.g., Claude Code style tools) as a first class part of your development process, including architecture exploration, implementation, testing, refactoring, and documentation, while maintaining full ownership of output quality and understanding their strengths and limitations.
• Implement and evolve agentic systems using frameworks such as Lang Chain, CrewAI, Pydantic
  
  AI, or equivalent, including tool orchestration, memory/state handling, and multi‑step reasoning workflows.
• Build scalable retrieval and inference pipelines: embedding workflows, vector databases, hybrid retrieval strategies, caching, and evaluation loops to balance accuracy, latency, and cost.
• Identify where agentic approaches provide leverage over conventional code and where they do not, making pragmatic, production minded tradeoffs across cost, accuracy, latency, and reliability.
• Design guardrails and failure‑mode mitigations for non‑deterministic systems, including prompt structure, validation layers, fallback strategies, and human‑in‑the‑loop patterns where appropriate.
• Integrate observability and evaluation into AI‑enabled features, monitoring correctness, drift, bias, and performance over time.
• Collaborate with architects, product managers, and designers to translate ambiguous requirements into robust technical designs.
• Contribute to shared libraries, internal tooling, and reference patterns that accelerate delivery of AI‑enabled features across teams.
• Participate in code reviews and design discussions, raising the bar for quality, reliability, and responsible use of AI across the engineering organization.
• Mentor other engineers on effective agentic coding practices, prompt design, and emerging patterns as adoption scales.
• Own AI‑enabled features end‑to‑end in production, from initial design and implementation through deployment, monitoring, on‑call support, incident response, and iterative improvement.

• 7+ years of professional software engineering experience, with a strong background building and operating SaaS platforms in production.
• Proven experience working at a SaaS company, contributing to multi‑tenant, cloud‑based systems.
• Hands‑on experience architecting or contributing meaningfully to SaaS platform architecture, including well‑defined service boundaries, API design, domain modeling (DDD), data modeling, and integrations across distributed systems.
• Advanced, practical experience using AI coding agents in day to day development, not just experimentation but real production work, with clear ownership of outcomes.
• Strong hands‑on experience with agentic systems and AI workflows, including:
• RAG architectures and retrieval pipelines
• LLM integrations, prompt engineering, and context engineering
• Agent orchestration and…