Forward Deployed Engineer
Take2.ai
Location
New York
Employment Type
Full time
Location Type
Hybrid
Department
Engineering
Compensation
- Base Salary $80K – $140K • Offers Equity
About Take2 AI
Take2 AI automates phone screens with AI agents.
Take2's AI Interviewers automate the end-to-end screening process - evaluating resumes, conducting phone screens, and scheduling next round interviews with qualified candidates. Our AI Interviewers help reduce overhead costs while boosting speed-to-hire and preventing mis-hires. For candidates, this guarantees they’re never left without a response and delivers a better experience, uncovering skills that go beyond the resume.
We are a team of Stanford GSB alums, backed by SemperVirens & Reach Capital. Our advisory board consists of ex CHROs of F500 companies such as Visa, HP, Disney & Google.
Want a sneak peek of what we are building? Check out this video!
About the Role
Take2 AI is hiring a Forward Deployed Engineer to design, launch, and continuously improve our AI Interviewers for customers. Our AI agents already conduct tens of thousands of structured candidate interviews each month.
This role sits at the intersection of voice/conversational agents, prompt + flow design, evaluation/scoring rubrics, and production iteration. You’ll work directly with customers to understand screening requirements, translate them into structured interviewer behavior, deploy agents into production, and improve performance based on real-world feedback and metrics.
This is a hands-on, highly analytical role for someone who enjoys turning ambiguous requirements into precise agent behavior, building rigorous evaluation approaches, and shipping improvements quickly in a startup environment.
What You’ll Do
Customer Onboarding & Requirements (Customer-Facing)
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).
Voice Agent Conversation Design (Prompts + Flows)
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.
Evaluation & Scoring Systems
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.
Deployment, Iteration, and Customer Feedback Loops
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.
Quality, Reliability, and Scale
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.
In Terms of Experience
Required:
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).
Preferred:
Familiarity with voice/conversational AI systems, especially real-time or high-volume environments.
Strong Python skills (APIs, data pipelines, eval harnesses, testing frameworks).
Hands-on experience with multiple LLMs (GPT, Claude, Gemini, LLaMA/Mistral, fine-tuned models).
Experience designing multi-step agents with state management and structured outputs.
Experience operating AI systems in production and iterating based on real-world performance metrics.
Prior startup experience (high ownership, fast iteration, ambiguity).
Bachelor’s degree in CS/Engineering/Math or related technical field — or equivalent practical experience.
Compensation Range: $80K - $140K
