Client Success and AI Deployment Lead

**Client Success and AI Deployment Lead** **Location:** Hybrid — Chicago, IL **(3+ days in office required)** **Job Type:** Full-time W-2 employee, subject to a 90-day introductory period **Internal Title:** Forward Deployed Engineer, Client Facing **About AviaryAI** AviaryAI builds AI agents that call and text members on behalf of credit unions, community banks and insurers. Our agents handle real conversations about real money in a highly regulated industry, across voice and text, with generative AI running both channels.

We’re backed by Y Combinator, growing fast, and our agents have made millions of calls. **About the Role** You take a signed contract and turn it into a live AI agent making real calls and texts. Then you keep improving it until it hits the client’s goals and stays there. You own the journey after the sale, from kickoff to long term impact. Most of your week is spent with client teams: running kickoffs, aligning stakeholders, walking through results, and earning the trust that makes the work possible.

This is also a hands on technical role. When the platform doesn’t do something a client needs yet, you don’t wait on a ticket. You build the fix yourself, scoped tightly to that client. When the ask is bigger than one client, you scope it precisely and hand it to engineering. **What You Will Do** - **Own client outcomes.** Agree on success criteria early, launch cleanly, and keep optimizing until performance targets are met and sustained. - **Lead AI deployments end to end.** Design, configure and launch agents.

Shape prompts, workflows, integrations and guardrails so agents perform reliably in production. - **Close the gaps yourself.** Write SQL, ship a script with Claude Code or Cursor, or build a small automation when a client needs something the platform can’t do yet. - **Create repeatable deployment systems.** Improve onboarding frameworks and document what works so every launch is faster and more predictable than the last. - **Solve problems across teams.** Work with Engineering to resolve technical issues, and translate system behavior into clear business implications for the client. - **Strengthen and expand client partnerships.** Use performance data to spot new use cases and bring them to the client. - **Inform the product.** You’re closer to production than anyone building the platform.

What you bring

back shapes what gets built next. **What We’re Looking For** Must haves: - **High agency.** You set the plan, follow through, and don’t wait to be told what’s next. - **Technically capable.** Comfortable shipping small scripts or automations against real production data. You’ve written prompts, evaluated AI outputs, and understand how data flows between systems. - **Strong communicator.** You can explain the same issue to an engineer and to a credit union executive without losing either. - **Client advocate.** You build trust quickly, manage competing priorities, and have a track record of long term relationships. - **Calm under pressure.** You resolve complex issues in high stakes situations without getting rattled. - **Fast learner.** You pick up new tools, concepts and domains quickly.

Nice to haves:

• - 1 to 3 years in implementation, solutions engineering, consulting, client success or a similar customer facing technical role - Experience in fintech, insurance or financial services - Experience in conversational AI, voice workflows or contact center technology **This Role Is Probably Not for You If** - You want to spend most of your day heads down writing code - You’d rather not be on client calls every week - You prefer managing relationships without getting into the data or the tooling yourself ### About the interview - Introductory Call (20–25 minutes): Meet our CEO and get to know each other.
• (Virtual) - Department Interview (30 minutes): Deep dive into the role and expectations.
• (Virtual) - Practical Assessment Interview (60-90 minutes): You will complete a short project and present how you would improve an onboarding process and identify “at-risk” clients using simple tools and AI assistance.
• (Virtual) - Final Interview (30-60 minutes per interview): Meet with the founding team.
• (In-person) - References and Offer.   ## Compensation The base pay range for this role is $90,000 – $130,000 per year.