Hybrid Forward Deployed Engineer

at Take2 AI

• Job title: Forward Deployed Engineer
• Job type: Full Time
• Experience level: Junior, Mid level
• Salary: $80,000 - $140,000 per year
• Degree requirement: Bachelor's Degree
• Location requirements: Hybrid, New York City, United States

About the role

• Forward Deployed Engineer designing and launching AI Interviewers for customers at Take2 AI. Involving customer onboarding, voice agent design, evaluation systems, and continuous iteration.

Responsibilities

• Lead technical onboarding with customers to understand roles, hiring goals, must-have signals, and constraints.
• Translate customer needs into structured interview flows, role-specific question banks, and scoring rubrics.
• Set clear expectations on what “good” looks like (pass/fail thresholds, evaluation rationale, interviewer tone and style).
• Design, build, and refine prompts and agent logic that drive interviewer behavior, question sequencing, probing, and candidate experience.
• Ensure interviewer conversations are consistent, role-relevant, and robust to edge cases (evasive candidates, unclear answers, noisy audio, interruptions).
• Implement multi-step structured interview flows with state management and guardrails.
• Design and maintain AI-based evaluation and scoring aligned to customer rubrics and hiring criteria.
• Improve accuracy, consistency, and explainability of scoring at scale (including calibration across roles/customers).
• Identify bias/fairness risks and contribute to mitigation strategies and compliant evaluation practices.
• Launch new customer interviewers into production and own iteration cycles from early rollout through steady-state performance.
• Use customer feedback + production metrics to prioritize improvements and deliver measurable outcomes.
• Communicate changes clearly to customers and internal stakeholders.
• Build and own lightweight QA/evaluation pipelines to measure conversation quality, scoring accuracy, and reliability before/after changes.
• Monitor production performance and partner with engineering to balance quality, latency, and cost tradeoffs.
• Contribute to standards and best practices for prompt quality, eval quality, and voice-agent reliability.

Requirements

• 2+ years working with LLMs, NLP systems, or AI agents in production.
• Demonstrated experience designing and deploying agent workflows (prompts + structured flows) that operate at scale.
• Strong understanding of prompt engineering, agent control, failure modes, and conversational edge cases.
• Experience building or contributing to evaluation/testing/QA frameworks for AI systems.
• Comfort being customer-facing: running technical discovery, translating requirements, and driving onboarding to production.
• Strong analytical mindset (accuracy, consistency, bias, calibration, and edge cases).

Benefits

• Offers Equity