Founding Engineer (AI & Agentic Systems)

Codexa is building an agent-first CRM. Instead of reps working a CRM by hand, our AI agents run the revenue operation itself: outbound, qualification, and pipeline management, end-to-end, replacing traditional SDR and AE workflows. The MVP is live, we have paying clients, and the core architecture is already running client campaigns. We're looking to hire a founding engineer to own the intelligence layer of the product. This person lives entirely on the agentic and AI side of Codexa: the orchestration that decides what every agent does next, the LLM systems behind it, and the voice infrastructure that runs live calls. It's an AI-focused seat, but not an AI-only one. We're building a full CRM, so you need real full-stack engineering behind you. **Compensation** This role starts on a fully deferred cash comp rather than a standard salary. It's a market-rate role with pay deferred and repaid at a premium once we hit a funding or revenue milestone. We're upfront that this is a real trade: less cash now, real upside as the company grows. Happy to walk through the specifics directly. **What you'd own** * The agentic orchestration layer: the state machine and decision engine that runs each lead end-to-end across email and voice, including our Next Best Action logic, escalation, and handoff rules * Our LLM stack: model integration and routing, prompt systems, tool and function calling, retrieval and vector memory, and the evals and guardrails that keep agent behavior safe and reliable in production * Voice AI: the real-time voice agent stack, from call orchestration and latency tuning to qualification on live calls * The reasoning and data enrichment pipeline as it scales from internal tooling into a productized platform * Application development around all of it: the backend services, data models, and APIs the agents run on * Engineering standards for how we build AI systems from the ground up, where your calls on frameworks and architecture will stick **What we're looking for** * Hands-on experience building agentic systems with orchestration frameworks like LangGraph and LangChain, not just calling an LLM in a loop * Strong applied LLM engineering: prompt design, tool and function calling, RAG, vector databases, and structured outputs, with real production experience * Voice AI experience: real-time voice agents, telephony, and the ability to structure and tune latency-sensitive call flows * Comfort integrating and routing across model providers (OpenAI, Anthropic/Claude, OpenRouter) and reasoning about cost, latency, and reliability trade-offs * Solid full-stack engineering: able to ship end-to-end across backend, data, and APIs (Node.js/TypeScript, Python, PostgreSQL, queues and workers) * Experience with multi-agent or event-driven architectures and state machines * Startup or 0-to-1 experience preferred, and comfortable with ambiguity and fast iteration * Based in Canada or the US with overlap in Eastern hours. **Strong pluses** * Experience with the Model Context Protocol (MCP) for giving agents controlled access to internal and external systems * LLM observability and evals: tracing, prompt versioning, and offline and online evaluation * Multi-tenant, workspace-isolated architecture at scale * Experience building enrichment or data pipelines that feed agent decisioning