Staff Engineer AI Agents

• Architect, build, and deploy production AI agents using modern agent frameworks (LangGraph, CrewAI, AutoGen, or equivalent), owning the full lifecycle from design to reliability in production
• Define the technical patterns and standards for how agents are built across the engineering org — you will be setting the playbook others follow
• Lead the rebuilding of core platform systems — including our onboarding/configuration system, integration framework, and AI performance analytics infrastructure
• Collaborate directly with the VPE and product leadership to translate product vision into agent architecture, and make high-stakes technical trade-offs with confidence
• Own agent reliability, observability, and continuous improvement — defining how we measure, monitor, and iterate on agent behavior in production
• Work across the stack (backend services, LLM orchestration, integrations, data pipelines) to ship agents that are robust and scalable
• Tame legacy code and lay down new foundations — patterns and architecture you create will be inherited by the engineers who come after you
• Be a close partner to the product and operations teams, turning their domain needs into intelligent automated workflows without requiring domain expertise upfront

• 5+ years of software engineering experience with a strong backend or distributed systems foundation
• Demonstrated experience designing and shipping AI agents in production — not just prototypes. You've owned agent systems that real users depend on
• Hands-on experience with at least one modern agent framework such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or a comparable orchestration layer
• Deep familiarity with LLM integration patterns — prompt engineering, tool/function calling, memory systems, retrieval-augmented generation (RAG), and agent evaluation
• Experience building reliable, observable agentic systems: tracing, error handling, fallback strategies, human-in-the-loop checkpoints, and graceful degradation
• Strong proficiency in Python and/or TypeScript — the languages our agents live in
• Ability to work across ambiguity and drive projects from problem definition through production deployment independently
• Clear, direct communicator who can translate complex technical architectures for non-technical stakeholders

• Experience with multi-agent systems — coordination patterns, agent-to-agent delegation, and conflict resolution
• Familiarity with vector databases and embedding strategies (Pinecone, Weaviate, pgvector, etc.)
• Prior experience at a startup or high-growth company
• comfort shipping fast and iterating in production
• Background in building self-serve platform or integration infrastructure
• Experience with workflow automation platforms or business process orchestration
• Experience with telephony integrations (Twilio or similar) and building voice-capable agents or chatbots across text and voice channels
• Familiarity with speech-to-text, text-to-speech, or real-time audio streaming pipelines in production AI systems
• Classical ML experience — supervised/unsupervised learning, feature engineering, model training and evaluation outside of LLM contexts

Competitive compensation package including meaningful early-stage equity