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Full-Stack Engineer Sales Optimization  ·  NLP & Predictive Atlanta, GA (Buckhead)   |   On-Site / Hybrid   |   Atlanta-Based Only, No Remote   |   Engineering Team Most AI companies sell tools. We deliver the outcome. Peach Pilot is an AI-Native Services (AINS) startup. Instead of selling software and leaving the work to the customer, we become the service provider and use AI to win, faster, better, and cheaper than a traditional firm, and we get paid when the results land. The customer buys an outcome, not a seat, and our system gets smarter with every engagement. We are starting with life insurance sales optimization: helping agencies sell more effectively and more durably by learning, from their own data, what actually separates good outcomes from bad ones, and putting that back in front of the humans doing the selling. Our first client engagement is live and funded. Peach Pilot is co-founded by Mario Montag (founder of Predikto, acquired by a Fortune 50, and an alum of McKinsey and PwC) and JP James (Hive Financial Assets, Georgia Tech, TITAN 100). We have a working platform with live infrastructure and a proven data-to-insights methodology. The Role You will join our engineering team as a senior full-stack engineer owning a core layer of the product: the real-time systems that take live sales calls, stream and process the audio, and turn them into signal the moment it happens. Our core application is Next.js and TypeScript . The near-term problem is concrete. We record tens of thousands of sales calls, and we are building the product that listens to them as they happen, reads sentiment and intent in real time, and coaches the human while the call is still live. Our data scientist handles the analysis of what a good call looks like. Your job is to build the engineering around it: the audio streaming, the live call processing, the telephony and dialer surface, and the client-facing application that puts it all in front of people who have never touched a terminal. If you have built real-time audio or telephony systems and want to do it at a startup where your work directly moves a customer's numbers, this is it. What You Will Own & Build Call Ingestion & NLP Extraction Pipeline Build the pipeline that ingests roughly 50,000 recorded calls and turns them into a validated, structured dataset. Transcription (ASR), then NLP and LLM-based extraction of the metadata that matters (entities, intents, objections and how they are handled, sentiment, script adherence, outcomes), each tied back to its evidence in the transcript. You own data quality (deduplication, enrichment, classification, validation) and the governance boundary: PII minimization at ingest and access control that is enforced, not assumed. Backfill runs in batch, and the same code runs live on new calls. Our data scientist leads the analysis of what a good call looks like; you build the pipeline that makes her findings run at scale. Analytics, Causation & Prediction Partner with our data scientist, who owns the core analysis, to productionize what she finds: the engineering behind the analytics that identify which behaviors correlate with durable outcomes, the causal methods that separate correlation from a real lever (randomized holdouts and uplift modeling, not feature importance alone), and the predictive models (calibrated risk and opportunity scores) that let us act ahead of time. You will own the feature store, model registry, and the discipline that keeps a prediction defensible. Live Transcript Processing in Applications Incorporate real-time transcript processing into the product. Streaming, low-latency coaching delivered to the human on the call, with human-in-the-loop governance and confidence-tiered nudges (act firmly, suggest softly, or stay silent). You are responsible for how that guidance reaches the user and whether it