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Forward Deployed Engineer

AviaryAI

Chicago, ILFull-timeSeen 1 day agoStill listed 1 day ago

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At a glance

Compensation
No compensation found
Location
Chicago, IL
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

AviaryAI builds voice agents for financial institutions. The Forward Deployed Engineer turns signed contracts into live AI agents, then improves them to meet client goals. The role combines technical implementation with client relationship management, building scoped fixes when platform capabilities fall short and escalating broader needs to engineering. It also feeds production insights back to product and engineering teams.

Skills & qualifications

RequiredNice to have

Skills

InitiativeScriptingAutomationPromptingAI Output EvaluationData FlowsSystems IntegrationCommunicationClient Relationship BuildingIssue ResolutionAdaptabilityLearning AgilityImplementationClient SuccessOperationsQuality AssuranceSupportFintechInsuranceFinancial ServicesConversational AIVoice WorkflowsContact Center Technology

Qualifications

1+ Years Experience

Full job description

Client Deployment & Success Lead (Forward Deployed Engineer) AviaryAI | Chicago, Illinois | In person About AviaryAI AviaryAI builds voice agents for credit unions, banks, and insurers — real calls, real members, real compliance requirements. Backed by Y Combinator, growing fast, millions of calls made. About the Role A forward deployed engineer takes a signed contract and turns it into a live AI agent making real calls and texts, then improves it until it achieves the client's goals. You sit between the client and the platform. 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 the problem precisely and hand it to engineering instead of hacking around it. This is a technical role that also manages the relationships, aligns the stakeholders, and earns the trust that makes the work possible. What You Will Do

  • Own deployment outcomes. Configure the agent: prompts, call flow, transfers, guardrails, SMS fallback — launch it, and optimize until it hits target and holds.

  • Build what's missing. When a client's problem needs more than config, write and ship the script or small automation that closes the gap. Know the difference between a fix that's yours to build and a problem that needs to go to engineering.

  • Create Repeatable Deployment Systems: Improve onboarding frameworks, document best practices, and refine internal processes so implementations become faster, more predictable, and easier to scale.

  • Cross-Functional Problem Solving: Collaborate with Engineering to resolve technical issues and maintain production performance, translating system behavior into clear business implications and next steps.

  • Strengthen and Expand Client Partnerships: Identify opportunities for improvement and expanded use cases based on performance data and evolving needs.

  • Inform Product Through Real-World Insights: Surface structured feedback from production environments to engineering and product teams to improve reliability, usability, and overall impact.

  • Feed the product. You're closer to production than anyone building the platform. What you bring back changes what gets built.

What We're Looking For Must-haves:

  • High-Agency Mindset: Takes initiative without waiting for direction. You proactively identify key outcomes, make a plan, and follow through to ensure measurable results.

  • Technically Fluent: Comfortable shipping small scripts or automations against real production data. Experience with prompting and evaluating AI outputs. And a functional understanding of data flows and how systems integrate.

  • Strong Communicator: Communicates effectively to both technical teams and executives by simplifying complexity without losing nuance.

  • Client Advocacy: Able to quickly build trust and navigate competing priorities. Proven ability to develop long-term relationships.

  • Adaptable Under Pressure: Skilled in resolving complex issues in dynamic, high-stakes environments.

  • Fast Learner: Quickly grasps new concepts, tools, and domains, accelerating the path to impact and staying ahead in evolving technical and business contexts.

  • Thrives in Fast-Paced Environments: You are energized by environments where priorities shift quickly, stakes are high, and your work makes a visible impact.

You don't need financial services or conversational AI experience — both are learnable fast. What matters more is judgment about how a real person reacts when things don't go as scripted. Nice to haves:

  • 1 - 3 years of experience in implementation, client success, operations, QA, or support.

  • Experience in fintech, insurance, or financial services

  • Experience in conversational AI, voice workflows, or contact center technology.

Why You’ll Love This Role You get to shape AI systems that are helping millions of people navigate their financial lives. You’ll be a part of a small, elite team where your contributions have a measurable impact on AviaryAI’s growth trajectory and direction.

How this job compares

Set against the 2,914 open Forward Deployed Engineer jobs on Olive Jobs, counted November 4, 2026.

Pay
  • This postingNot listed
  • Illinois median$152–265K/yr69 salary ranges
  • US median$31–91/hr62 hourly ranges
Openings
Olive Jobs lists 80 open Forward Deployed Engineer jobs in Illinois and 2,914 across the US. 6% of them nationwide are listed as remote or flexible.
Hiring the most in Illinois
Experience
This posting asks for no prior experience — less than three in four Forward Deployed Engineer postings that state a minimum ask for (median 5 years, across 2,556 postings).
Education
630 of the 2,914 open Forward Deployed Engineer jobs (22%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 4, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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