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# Senior Full Stack Developer

- **Company:** NxT Level
- **Location:** Nashville, TN, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, JIRA, Continuous Integration, Software Debugging, Github, Python (Programming Language), PostgreSQL, Node.Js, Redis, OpenAI, Next.js, Data Streaming, TypeScript, WebSocket, ReactJS, Retrieval-Augmented Generation, Large Language Models, Firebase, Agentic-AI, Fastapi, Cloudflare, Apache Kafka, Graphql, Front End Software Development, Invoking Functions, Amazon Simple Queue Service (SQS), Software Version Control, Docker
- **Published:** November 6, 2026
- **Apply:** https://www.adzuna.com/details/5448604963

## About the Role

* Have 4+ years building full-stack products (or equivalent portfolio/hacker track record).
 * Are fluent in a modern web stack (e.g., TypeScript/Node, Python, React/Next; Postgres/Redis; REST/GraphQL).
 * Have shipped LLM/SLM features (tool use, RAG, function calling, evals, latency/cost tuning).
 * Can design simple, resilient backends; write clean, testable code; and deploy via CI/CD to a major cloud.
 * Love debugging with data: logs, traces, metrics; you instrument before you guess.
 * Communicate crisply, ask sharp questions, and default to action.
 * Thrive in ambiguity; you don't need a JIRA novella to start building.

Nice to have

 * Vector DBs, embeddings, prompt/version management, offline evals.
 * Agent frameworks (e.g., OpenAI tools, LangGraph, custom planners/executors).
 * Queueing/event systems (e.g., Kafka, SQS), WebSockets, streaming.
 * Security and privacy basics (authn/z, secrets, PII handling).
 * Experience with low-cost scrappy stacks (Cloudflare, Fly.io, Supabase, Firebase)., 2. Builder exercise (home or live, 2-4 hrs): ship a tiny agent or automation; explain trade-offs.
 3. Technical deep dive (60 min): architecture, data modeling, reliability, AI evals/cost.
 4. Team fit (30 min): collaboration, feedback loops, "why before what."

## Description

* Prototype at lightning speed: Build and ship POCs, internal tools, and production features in days-not weeks.
 * Work with LLMs & SLMs: Integrate, evaluate, and fine-tune models; design agentic workflows that reduce manual work.
 * Automate the boring stuff: Sniff out bottlenecks, redundancies, and paper cuts; replace them with lightweight automations.
 * Balance build vs. buy: Pragmatically choose off-the-shelf services vs. custom code; optimize for speed, cost, and learning.
 * Own the stack end-to-end: APIs, data models, frontends, deployments, instrumentation, and on-call for what you build.
 * Collaborate without ego: Pair with design, product, and GTM to clarify the "why," define thin slices, and ship continuously.
 * Ruthlessly iterate: Be comfortable restarting weekly if needed; measure outcomes, not lines of code.

Outcomes (how we'll measure success)

 * 2-3 prod-quality launches/month from idea * shipped.
 * Clear learning loops: each release produces measurable signal (conversion, retention, time-saved).
 * Automation ROI: hours saved/team/week; decreased cycle time; reduced ops tickets.
 * Agent impact: at least one agent in steady use by internal or pilot users within first 60 days., * BE: Node/TypeScript and/or Python FastAPI
 * Data: Postgres, Redis/Upstash, optional vector store
 * Infra: Vercel/Fly.io/Cloudflare + Docker; CI/CD (GitHub Actions)
 * AI: OpenAI, Anthropic, local SLMs when useful; evaluation harness + prompt/version control

How we work

 * Learn > Perfect: Ship thin slices, get signal, iterate.
 * Write it down: Short RFCs * prototype * user feedback within days.
 * Builder culture: No rockstars, no heroes-just ownership and curiosity.
 * Time-zone friendly: Async first; quick huddles when needed.