Forward Deployed Engineer

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🕒 January 29

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Take2 AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

🤖 Artificial Intelligence

👥 HR Tech

🎯 Recruiter

💰 Seed Round on 2024-04

Artificial Intelligence • HR Tech • Recruitment

Take2 AI is a company that specializes in automating high-volume recruiting and training through AI-generated agents. These agents effectively vet talent for essential skills, behavioral attributes, and cultural fit while providing valuable performance data to employers. By leveraging real-world simulations tailored to specific job roles, Take2 AI enhances the recruitment process, reducing time-to-hire and improving employee retention.

📋 Description

• 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