Founding AI Engineer (Part Time) - Prompt Engineering & LLM Applications
Part-Time Founding AI Engineer - Prompt Engineering & LLM Applications
About Y22 AI
Y22 AI is building an AI sales training and call intelligence platform that helps sales teams identify what their top reps are doing differently, score real sales calls, and turn rep weaknesses into targeted AI roleplay training.
Our platform helps reps practice against AI prospects that mirror the exact buyers, titles, companies, objections, and sales situations they face in the real world.
We are looking for a part-time Founding AI Engineer with strong prompt engineering and LLM application development experience to help build the core intelligence layer behind Y22.
This is an early-stage, equity-based role for the first 6 months. We are looking for someone who wants meaningful ownership, can move fast, and is excited to help build a category-defining AI sales coaching platform from the ground up.
What You’ll Work On
- Create realistic AI sales prospects through advanced prompt engineering
- Tune AI prospect behavior by buyer type, title, industry, company size, pain points, objections, call type, and training goal
- Build prompt systems that make roleplays feel realistic, challenging, adaptive, and useful for sales reps
- Turn real sales calls into structured coaching insights
- Score sales conversations using Y22’s sales performance rubric
- Analyze transcripts for rep strengths, weaknesses, objections, talk tracks, missed opportunities, and next steps
- Generate personalized roleplay scenarios based on each rep’s performance gaps
- Build prompt templates, prompt chains, evaluation workflows, and structured output systems
- Create RAG pipelines over customer sales calls, product docs, ICP docs, sales playbooks, objection libraries, and training materials
- Improve AI accuracy, consistency, relevance, hallucination resistance, and output quality
- Support future real-time sales assistant workflows
Responsibilities
- Design, test, and iterate prompts for AI roleplay, call scoring, coaching insights, and sales simulations
- Build prompt systems that control tone, difficulty, objection patterns, buyer resistance, personality, and conversation flow
- Develop LLM-powered backend workflows using Python
- Create structured outputs for scorecards, coaching plans, roleplay scenarios, and rep performance insights
- Build transcript analysis and scoring workflows grounded in call evidence
- Design retrieval workflows using embeddings, vector databases, and customer-specific knowledge bases
- Develop evaluation processes to measure prompt quality, hallucination risk, relevance, realism, and consistency
- Monitor model outputs and improve prompts based on real user behavior and feedback
- Work closely with the founder on product direction, customer feedback, and roadmap priorities
- Move quickly while maintaining strong engineering standards
Required Qualifications
- Strong prompt engineering experience with LLMs
- Strong Python experience
- Experience building LLM-powered applications
- Experience with OpenAI, Anthropic, Grok, or similar model providers
- Ability to design prompts for structured outputs, roleplay behavior, scoring, classification, summarization, and coaching
- Understanding of prompt testing, prompt versioning, temperature testing, and output evaluation
- Experience with RAG, embeddings, retrieval, and vector databases
- SQL/database experience
- Backend/API development experience
- Docker experience
- Working knowledge of AWS or GCP
- Ability to evaluate AI outputs for accuracy, relevance, hallucination risk, and usefulness
- Strong product instincts and ability to operate in an early-stage environment
- Comfortable working part-time in a fast-moving startup
Nice to Have
- Experience building AI roleplay, simulation, tutoring, coaching, or conversational training systems
- Experience designing AI personas, buyer behavior, objection handling, or adaptive conversation flows
- Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks
- Experience with voice AI or real-time conversation systems
- Experience with prompt injection prevention and AI safety guardrails
- Experience with AI evaluation, model monitoring, and output logging
- Experience with fine-tuning, LoRA, PEFT, or model optimization
- Kubernetes or production infrastructure experience
- Experience with sales tech, call intelligence, CRM integrations, coaching tools, or enablement platforms
Who You Are
- You are excellent at getting LLMs to behave consistently and usefully
- You understand that prompt engineering is not just writing instructions — it requires testing, iteration, evaluation, and product judgment
- You can take rough product ideas and turn them into working AI workflows
- You care about building AI that is accurate, realistic, useful, and reliable
- You are comfortable with ambiguity and fast iteration
- You think like a product builder, not just an engineer
- You can balance speed with engineering quality
- You are excited by the idea of helping sales teams improve rep performance using AI
- You want meaningful ownership in an early-stage company
Compensation / Structure
This is a part-time, equity-based role for the first 6 months. The goal is to convert this into a paid role as Y22 continues to grow revenue, customers, and funding options. The right person will be treated as a core early builder with meaningful ownership and influence over the product, AI behavior, prompt architecture, and technical direction.
How to Apply
Please submit:
- Your GitHub
- A short summary of AI, LLM, prompt engineering, backend, RAG, or product systems you have built in the past
- Your approximate weekly availability
Skills
- Prompt Engineering
- Large Language Models
- Generative AI
- Python
- LLM Applications
- Vector Databases
- SQL
- Docker
- AWS
- Google Cloud Platform
- Natural Language Processing
- LangChain
- LangGraph
- LlamaIndex
- MLOps
- AI Evaluation
- Conversational AI
- AI Agents