# Principal Software Engineer, Applied AI

**Company:** [Highspot](https://hotfix.jobs/companies/highspot)
**Location:** Seattle, WA
**Role:** ML Engineering
**Experience:** 8+ years
**Skills:** Python, Java, TypeScript, AWS, Azure, GCP, Llm Evaluation Frameworks, Agentic Ai Systems, Context Engineering, Retrieval Pipelines
**Posted:** 2026-06-15

> Principal Software Engineer leading technical direction for Generative AI and Agentic systems at enterprise scale. Owns AI platform architecture, builds evaluation infrastructure, and drives model strategy across the organization.

## Job Description

## What You'll Do

- Design and build agentic AI systems that orchestrate multi-step workflows across heterogeneous enterprise content – documents, CRM data, analytics, and more – to deliver contextual, actionable answers for sales teams.
- Own the AI platform architecture – define the patterns, abstractions, and guardrails that enable multiple engineering teams to ship AI-powered features safely and independently.
- Build evaluation and observability infrastructure for non-deterministic systems – including automated regression testing, LLM-as-judge pipelines, and production quality monitoring – so the team can ship AI features with confidence.
- Drive model strategy and cost efficiency – evaluate and route across model providers, optimize context windows, and make principled latency/quality/cost tradeoffs at enterprise scale.
- Raise the AI engineering bar across the organization – not just within your team, but across engineering. Coach engineers on applied AI best practices, build shared tooling, and cultivate a culture where AI fluency is widespread.
- Drive operational excellence – ensure enterprise-grade reliability, security, and performance for all AI-powered features in production.
- Communicate complex technical concepts clearly to both technical and non-technical audiences, and translate business needs into actionable engineering investments.

## Your Background

**What will set you apart:**

- Demonstrated depth in shipping production agentic AI systems – you've built multi-step, tool-using agents that operate on real data at scale.
- Deep expertise in context engineering: retrieval pipelines, ranking, prompt orchestration, and the tradeoffs involved in assembling context for LLMs over large, diverse document corpora.
- Hands-on experience building evaluation frameworks for non-deterministic AI systems – you understand why this is hard and have opinions on what works (synthetic evals, human-in-the-loop, LLM-as-judge, production monitoring).
- Track record of designing systems that balance quality, latency, and cost – including experience with model selection, routing, and optimization across providers.
- Strong instinct for platform thinking: you know how to build abstractions that accelerate other teams without over-constraining them.

**Foundations:**

- 8+ years of professional software engineering experience, with significant time spent on distributed, data-intensive production systems.
- Strong programming skills in Python, Java, TypeScript, or equivalent. You're comfortable across the stack.
- Experience developing and operating cloud services at enterprise scale (AWS, Azure, or GCP).
- A track record of full product lifecycle ownership – from technical design through iterative shipping to production operation.
- Experience mentoring engineers and building collaborative, high-performing teams.
- Strong cross-functional collaboration skills — you work effectively with ML researchers, data scientists, product managers, and business stakeholders with different backgrounds and priorities.

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**Canonical:** https://hotfix.jobs/jobs/740d49c2-8d7c-48ea-b1fd-f729d05d1308