Software Engineer, AI Applications

Ema is building the agentic AI operating system for enterprises. We help some of the world’s largest organizations transform deeply manual, brittle business processes into reliable, measurable, production-grade automated systems using AI agents, integrations, and human-in-the-loop UX. At Ema, success means real workflows running in production, used daily by business teams, with measurable outcomes. We’re founded by leaders from Google, Coinbase, and Okta, backed by top-tier investors, and scaling rapidly. As we grow, we’re building a team of engineers who don’t just ship code — they own outcomes. Customer Value Engineering is Ema’s forward-deployed, production-focused engineering group. CVE engineers sit at the intersection of Applied AI systems, real customer business processes and enterprise-grade reliability, security, and integrations. In this role you will work directly with customers and internal product/engineering teams to design, build, deploy, and improve agentic systems that actually move business metrics. If you want to move beyond demos and prototypes and learn how real AI systems behave in production this role is ideal for you. WHAT YOU’LL WORK ON - Design agentic workflows that map customer business processes to multi-agent systems with clear success criteria - Build and deploy AI applications using Ema’s platform: agents, tools, integrations, human-in-the-loop workflows - Implement integrations with enterprise systems (CRM, ticketing, data stores, internal APIs) - Debug production issues across the stack — model behavior, orchestration logic, permissions, data quality, UX - Run evaluations using golden datasets- test data generation, offline tests, regression checks, and real user feedback - Collaborate closely with customers (Ops, IT, business users) to deliver measurable value post launch - Partner with Product & Core Engineering to feed learnings back into the platform and improve reusability Who you are - 3+ years of production software engineering experience - At least one real production deployment of a GenAI/LLM-powered system (not just POCs) - Strong programming skills in Python and/or TypeScript - Practical experience with prompt and instruction design beyond basics , Tool/function calling and structured outputs - Practical experience with Retrieval and grounding (RAG, embeddings, chunking strategies) - Practical experience with Human-in-the-loop workflows and safe rollout patterns - Practical experience with validation techniques (golden sets, offline evals, error analysis) - Experience integrating with enterprise systems via APIs (REST/JSON), auth (OAuth, service accounts) - Comfort working with real customer data and operational constraints - Clear written and verbal communication with technical and non-technical stakeholders