Senior Software Engineer

Ozmo is a growing technology company transforming how enterprises leverage AI to deliver automated outcomes at scale. They are seeking a Senior Software Engineer to build and ship AI-first software, collaborating with product, architecture, and engineering teams to design scalable SaaS features that integrate generative AI capabilities into production systems.

Responsibilities:

• 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 LangChain, CrewAI, PydanticAI, 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

Requirements:

• 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 tool-chaining, Evaluation and observability for AI outputs
• Familiarity with agentic frameworks such as LangChain, CrewAI, PydanticAI, or similar, and the judgment to know when to extend, replace, or simplify them
• Deep understanding of software engineering fundamentals, including SOLID principles, clean architectural layering, common design patterns, testing strategy, and performance optimization
• Experience building and operating production systems with strong engineering discipline, including testable system design, observability, progressive delivery, and reliability patterns that reduce blast radius and enable safe iteration
• Comfort operating in cloud-native environments (AWS, Azure, or GCP), including microservices, event-driven architectures, CI/CD, and production monitoring
• Experience designing secure, multi-tenant SaaS systems, including access control patterns, data isolation, and defensive design practices appropriate for AI-enabled applications
• Strong communication skills, able to explain complex technical and AI-driven behavior clearly to engineers, product partners, and stakeholders, and to mentor other engineers through code reviews, design discussions, and thoughtful technical guidance
• A mindset of continuous learning, experimentation, and responsible innovation, especially as agentic capabilities evolve rapidly
• While a Bachelor's degree is preferred, we place greater value on demonstrated experience and impact