AI deployment architect - New York

We are hiring AI deployment architects to configure, deploy, and evolve our agents for enterprise customers. This role sits at the intersection of product, engineering, and customer delivery ; you will translate business requirements into robust configurations, ensure each deployment reflects client needs, and iterate rapidly to maintain high performance and system stability.

You will be a primary technical partner to our customers, guiding them through configuration decisions, troubleshooting complex behaviors, and shaping how they design and operationalize AI-driven screening. You will also act as a critical feedback conduit between the field and the product team, surfacing patterns that should be platformized and validating new capabilities with real-world customers.

This is a highly technical & hands-on role. As deployments accelerate across industries and geographies, you will help define the standards, tools, and best practices that make our agents scalable.

What you will do

Configuration and deployment

• Build and adapt screening flows based on customer jobs and requirements.

• Configure state prompts, tone parameters, voice selection, transitions, and conditional logic.

• Set up and maintain custom vocabularies for ASR when relevant.

• Prepare and run demos; support pilot implementations from start to finish.

Troubleshooting and iteration

• Analyze conversation transcripts and identify sources of errors or drift.

• Run isolated state tests for targeted debugging.

• Iterate rapidly on prompts and configurations to improve performance.

• Use SQL to investigate behavioral patterns, identify systemic issues, and validate improvements.

Client partnership

• Advise customers on screening design, personas, and best practices for AI-driven interviews.

• Communicate technical concepts, limitations, and trade-offs clearly.

• Manage expectations during pilots; build structured feedback loops that drive continuous improvement.

• Act as a trusted guide throughout deployment and iteration cycles.

Product collaboration

• Surface recurring field issues that should become productized solutions.

• Contribute insights that shape new configuration surfaces, evaluation tools, and system-level capabilities.

• Partner with product and engineering teams to test new features with selected customers and validate readiness for scale.

What makes this role unique

• You sit closest to real-world usage; your insights will directly shape how our agents evolve.

• You bridge product and customer needs, ensuring enterprise deployments remain robust, predictable, and high performing.

• You influence how AI-driven hiring is operationalized across the world’s leading companies.

• You will help define repeatable playbooks, tools, and standards that allow the deployment function to scale.

• As the first hire fully dedicated to this function, you will shape the boundaries of the role itself and set the industry bar for what excellence looks like in full-deployment engineering for conversational AI.

Experience

• Graduated from top engineering school or business/engineering dual-degree

• Prior client-facing technical experience, ideally supporting enterprise implementations.

Technical skills

• Hands-on work with conversational AI, LLM prompting, applied ML models, or workflow-based configuration.

• Ability to debug state logic, model outputs, and configuration inconsistencies.

• SQL proficiency for analytics and performance investigation.

• Comfort with light scripting and structured configuration formats.

Analytical and product mindset

• Strong ability to reason about system constraints and edge cases.

• Ability to distinguish between local configuration work and product-level feature needs.

• Structured approach to experimentation and iteration.

Client-facing abilities

• Clear and concise communication with both technical and non-technical stakeholders.

• Ability to present, educate, and manage expectations during pilots and demos.

• Confidence in advising customers and steering conversations.

• Stage 1 - Screening call with our agent (15 min)

• Stage 2 - Hiring manager interview (45 min)

• Stage 2 - Implementation lead interview (45 min)

• Stage 3 - Deep-dive technical interview (60 min)

• Stage 4 - Founder interview (45 min)

• Stage 5 - Offer and alignment discussion