Lead AI Forward Deployed Engineer

About the Team - BizApps Agentification

The Bizapps Agentification team sits at the intersection of AI, business operations, and product engineering. We are building the next generation of intelligent process automation — replacing manual, repetitive business workflows with AI agents that think, decide, and act. This is not incremental automation; it's a ground-up rethinking of how internal functions (Sales, HR, Finance, RevOps) operate using agentic AI.

What You'll Do

• Own Discovery for Your Domain: Own the domain roadmap — sequence the entire agentification program for your function by ROI and dependency, not just the next workflow.
• Set Architecture Standards: Hold architecture authority for the domain — review every agent design before build begins.
• Stay Hands-On Where It Matters Most: Take the hardest unsolved technical problem on the team and pair with an FDE to crack it — you are not the highest-volume coder, but the deepest technical thinker on the pod.
• Own Business Outcomes: Be accountable for domain-level metrics: total hours automated, error reduction, business team satisfaction, and adoption rate.
• Build the Platform: Champion platform extraction after every workflow delivery and run the platform retro cadence for your pod.
• Build the Team: Build FDE capability — specifically the discovery/PM muscle most engineers lack. Coach at least 2 FDE-1s to FDE-2 through structured, hands-on development.

What We're Looking For:

• Must-Haves: 6+ years of experience with demonstrated multiplier orientation — you've made others around you measurably better, not just shipped your own work. A track record of running discovery independently: sitting with a business team, mapping their process, scoping the automation target, and defining success metrics without a PM handing you a spec. Architecture-level ownership of at least one production system — you can design agent topology, tool-calling chains, human escalation points, and feedback loops, and defend the tradeoffs. Strong Python fundamentals and hands-on experience integrating LLMs (OpenAI, Anthropic Claude, Gemini, or similar) into production systems — you can still pair on the hardest bug in the codebase. Experience leading or informally mentoring engineers — you can point to specific people whose scope grew because of you. Comfort operating as the business-facing owner of outcomes: defining metrics, diagnosing whether underperformance is a design, data, or adoption problem, and acting on it.

• Good to Have: Prior experience as a technical lead, EM, or Principal/Staff engineer in a fast-moving product or platform team. Experience with agentic frameworks — LangChain, LlamaIndex, CrewAI, AutoGen, or equivalent — and RAG pipeline design. Familiarity with enterprise systems integration (Salesforce, HubSpot, or similar CRM/ERP platforms). Experience presenting technical roadmaps to non-technical executive stakeholders (CRO, CFO, department heads). A background that spans at least two of Discovery, Workflow Architecture, and Build & Ship at a senior level — this role does not suit engineers who have only ever received a defined spec.