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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 earns trust or breaks their flow.

Client-Facing Dashboards & Insight Delivery

Build the applications and interfaces that deliver the insights, the moment a client sees what is driving their results, backed by their own data, in plain language with rich visual context. These surfaces must be repeatable and deployable across every engagement through a per-client config layer. This is what sells the engagement and earns client trust.

The Stack

• Core application: js, TypeScript, Tailwind CSS, with charting via Plotly, D3, or Recharts. This is what we build in every day.
• Real-time audio and telephony: audio streaming, live call processing, in-browser calling, dialer integration, speech-to-text. This is the heart of what we are hiring for.
• NLP: real-time sentiment, intent and objection detection, entity extraction on live and recorded audio.
• Backend and data: js and TypeScript for the application. Python where it helps for audio and data scripting, though it is not a hard requirement. LLM APIs (Anthropic Claude, OpenAI) for structured extraction and coaching logic.
• Infrastructure: Google Cloud Platform, GitHub Actions CI/CD, Docker.

Who You Are

What matters most

• Real-time audio, telephony, or live call experience. You have built systems that stream or process audio, integrate a dialer, handle in-browser calling, or run live speech transcription. This is the single most important qualification and the hardest gap for us to fill.
• Strong Next.js and TypeScript. You build polished, client-facing interfaces that non-technical users trust and use, and you own the frontend end to end.
• Some hands-on NLP. One to two years is enough. Real-time sentiment, intent, or extraction on conversation data. You do not need to be a research-level NLP specialist. Our data scientist owns the deep analysis.

Experience

• 5+ years professional software engineering. A strong mid-to-senior engineer, not a specialist we have to manage. We have a strong bench in John, Chris, and Jeff, so we need someone who slots in and contributes, not someone we mentor from the ground up.
• Depth over dabbling on the AI and audio side. If your telephony or NLP experience comes from side projects or contract work rather than a day job, that counts, and we like builders who work on this in their own time. What we want to see is real depth: months of sustained work, something built end to end, not thirty days helping a friend.
• Atlanta based, or willing to relocate. This is an on-site role in Buckhead. We strongly prefer local. For the right person with very relevant experience we can offer modest relocation support.

Nice to Have

• UX or product design sensibility, enough to build a clean interface without waiting on a designer.
• Experience with LLM-based structured extraction from conversation or documents.
• Google Cloud Platform, or comparable AWS or Azure experience that transfers.

What Makes This Different

You are joining a proven founder's second company with established domain credibility. We have a working platform with live infrastructure and a first client engagement already in motion. You will have access to production data, live workflows, and real compliance requirements from day one.

This is an AINS company. We get better with every model release and every engagement, because each one enriches the data and sharpens the system for the next. You are not building features for a backlog. You are building the engine that learns how humans sell and makes them measurably better at it.

Compensation & Benefits

• Compensation: Commensurate with experience
• Benefits: Comprehensive medical, dental, and vision, plus 401(k) and flexible PTO
• Location: Atlanta, GA (Buckhead), on-site or hybrid. This role is for Atlanta-based candidates only. Remote applicants will not be considered.

• Location: Atlanta, GA (Buckhead), on-site or hybrid. This role is for Atlanta-based candidates only. Remote applicants will not be considered.