Lead pilots end-to-end: Scope success criteria, configure sandbox environments, and iterate rapidly to hit ROI targets in ≤ 90 days.
Design agent workflows: Author multi-step prompts, retrieval pipelines, and decision logic that plug into CRMs, ERPs, and custom APIs via our MCP framework.
Build secure integrations: Stand up data connectors and authentication flows (OAuth 2.0, SCIM, SAML) that give agents real-time context while meeting SOC 2 & HIPAA controls.
Operationalize at scale: Containerize and deploy agents on Kubernetes or customer VPCs; set up monitoring, A/B evaluation, and guardrails for hallucination and PII leakage.
Drive feedback loops: Surface customer insights to Product & Research; influence roadmap priorities around tooling, guardrails, and vertical templates.
Enable self-sufficiency: Deliver workshops, runbooks, and best-practice playbooks so clients can extend and govern agents post-go-live.
Requirements
4+ years in forward-deployed engineering, solutions architecture, or technical consulting for SaaS/AI products.
Proficiency in Python, Go, JS/TS plus hands-on experience with LLM frameworks (LangChain, RAG, vector search).
Cloud-native skills across AWS/GCP/Azure; comfortable with Docker, Helm, Terraform.
Strong communicator who can whiteboard with engineers at 10 AM and brief the C-suite at 4 PM.
Thrive in ambiguity; bias for action and a “customer-in-control” mindset.
Telephony stack knowledge (WebRTC, SIP, Twilio).
Experience deploying chatbots or voice bots at >10K daily conversations.
Contributions to open-source AI agent frameworks.
Benefits
Competitive benefits and perks
Robust training program
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.