Senior Software Engineer, Backend - AI Powered Products

TradeTrax; Phoenix (AZ); On-site; USD 140,000 - 200,000; Full time

Job summary

TradeTrax is hiring a senior software engineer to build and run the production AI pipeline behind a new feature for a production homebuilders platform. The role focuses on engineering around non-determinism in LLMs, instrumenting workflow, and defining quality metrics.

You will build the production backend for the AI pipeline (STT/LLM orchestration), implement evaluation layers, and operate scalable AWS services with CI/CD and Docker, with opportunities to grow into broader backend work.

Qualifications

• Senior backend engineer with strong Python experience and FastAPI or equivalent.
• Production experience running services on a major cloud with CI/CD, Docker, and ops practices.
• Experience taking a non-deterministic component (LLM or probabilistic system) into production with instrumentation and evaluation.
• Ability to learn unfamiliar domains quickly and influence team practices.
• Deep experience in LLM orchestration and evaluation infrastructure.
• Claude Code-centric or comparable agentic workflows with demonstrable impact.

Responsibilities

• Build and operate the production backend for the AI pipeline, including STT and LLM orchestration and the services around them.
• Develop instrumentation and evaluation layer with quality metrics and regression/eval harness.
• Treat the LLM as a calibrated dependency and optimize it over time.
• Create scalable backend services on AWS (Lambda, API Gateway, Docker, CI/CD).
• Evaluate and tune STT and LLM providers against internal metrics.
• Extend into broader backend platform engineering after production readiness.
• Set an example for AI-assisted engineering within the team.

Skills

Python

FastAPI

REST API

Distributed systems

CI/CD

LLM orchestration

Non-deterministic system handling

AWS

Backend engineering

Tools

Docker

AWS

Lambda

API Gateway

Job description

TradeTrax is a jobsite intelligence platform for production homebuilders. We capture real-time field data from builders and trades and turn it into the insights that drive cycle time compression, trade accountability, and operational performance. Our data is changing how the residential construction industry makes decisions.

Summary

We're hiring a senior software engineer to build and run the production AI pipeline behind a new feature, and to grow into broader backend work over time.

The defining challenge of this role is engineering around non-determinism. An LLM in the application path doesn't behave like a deterministic service. We need someone who treats that as an engineering problem, instrumenting the workflow, defining the right quality metrics, and calibrating relentlessly, rather than as a black box to be trusted or feared.

We are early in putting LLMs into production. We're not looking for someone with all the answers about voice or ASR. We're looking for a strong engineer who can build the measurement and feedback loops that turn a non-deterministic component into a reliable product feature, and who raises the whole team's game by example.

What you'll do

• Build and operate the production backend for the AI pipeline, including STT and LLM orchestration and the services around them, working within the existing backend team and its architecture.
• Build the instrumentation and evaluation layer: define quality metrics (edit rate, normalization drift, transcription accuracy, field-audio performance) and the regression/eval harness that lets us iterate on prompts and providers with confidence rather than vibes.
• Treat the LLM as a measured, calibrated dependency. Establish the feedback loops that let us optimize it over time.
• Build and operate scalable backend services on AWS (Lambda, API Gateway, Docker, CI/CD).
• Evaluate and tune STT and LLM providers against our own metrics.
• After this feature reaches production readiness, extend into broader backend platform engineering.
• Set the example for agentic, AI-assisted engineering on the team, and help us build that capability as a company.

Must have

• Strong backend engineering fundamentals: senior-level Python, FastAPI or equivalent, REST API and service design, distributed systems.
• Production experience running services on a major cloud. Solid CI/CD, Docker, and operational practices.
• Has taken a non-deterministic component, an LLM or a similar probabilistic system, into production and built the instrumentation and evaluation to make it behave reliably. This is the discipline the role is built around, so it's the one thing we won't compromise on.
• The range to learn unfamiliar domains fast. We'd rather hire a great backend engineer and have them learn the voice stack than hire a voice specialist who's a weaker engineer.
• Depth in LLM orchestration and evaluation/regression infrastructure. You've built these, not just used them.
• A Claude Code-centric (or comparable agentic) workflow, with a track record of influencing how a team works by example.
• Thought leadership on AI-in-the-loop engineering. Opinions formed from shipping, not slideware.

Nice to have

• Direct experience with ASR providers (Whisper, Deepgram, AssemblyAI) or audio pipelines. Useful, not required; learnable on the job.
• Bilingual or multilingual NLP experience.
• Hosted LLM API experience (Bedrock, OpenAI, Anthropic, Vertex).
• MLOps and AI infrastructure monitoring.
• Comfort in TypeScript / Node.js environments (parts of our stack live here).