> Markdown version of [/jobs/ext/4626862-builder-senior-software-engineer-ai](https://www.wearedevelopers.com/jobs/ext/4626862-builder-senior-software-engineer-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Builder - Senior Software Engineer, AI

- **Company:** Reevo, Inc.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Automated Storage and Retrieval Systems, Operational Databases, Software Safety, Search Technologies, Software Engineering, Reinforcement Learning, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Build Management, Machine Learning Operations, Human in the Loop
- **Published:** November 7, 2026
- **Apply:** https://www.careerbuilder.com/job-details/builder-senior-software-engineer-ai-santa-clara-ca--39d25855-dd18-4543-976c-e26aeb9849ab

## About the Role

Software Engineering, Artificial Intelligence (AI), Automation, Marketing, Business-to-Business (B2B), Sales Operations, Mentoring, Memory Hardware, Artificial Intelligence (AI), Reporting Dashboards, * 5+ years of software engineering experience, with a track record of building and shipping production AI/ML systems

 * Strong expertise in LLMs, RAG, vector databases, embeddings, and semantic search
 * Hands-on experience with prompt engineering, fine-tuning, and evaluating AI systems, plus the judgment to improve them based on the results
 * Experience deploying and monitoring AI systems in production, with working knowledge of AI safety practices
 * Strong communication skills, with the ability to explain AI concepts to technical and non-technical stakeholders
 * Bonus: real depth in one or more of memory and retrieval, agentic code execution and sandboxing, evaluation on production data, model training (fine-tuning to RL), or running agents in production at scale

## Description

The AI team builds the agents at the core of our platform. They track every signal on a deal as it arrives, work out the next move, and hand reps a drafted action to approve. Most of the team's work goes into three hard problems: memory, evaluation, and agent infrastructure.

We're looking for engineers who are self-motivated to a fault, obsessed with ownership and craft, and drawn to the biggest problem in the room. We'd rather hire someone who took an ambitious bet and failed than someone who played it safe and shipped on schedule.

What You'll Do:

 * Design and build memory and retrieval systems, including RAG, that stay fast and relevant at enterprise data volume
 * Build evaluation systems that hold up on messy, real production data, so results are reliable enough to gate a launch on
 * Design AI-driven interfaces that adapt to each org and user role instead of serving one generic dashboard
 * Train and improve models, from fine-tuning to reinforcement learning: design tool and agent interfaces clean enough to RL against, run the rollouts and deployments yourself, and build the data collection and labeling behind them
 * Build infrastructure for running agents in production at scale: durable execution, background jobs, and Human-in-the-Loop (HITL) checkpoints, with long-running workflows that survive crashes, redeploys, and retries
 * Build sandboxed environments for agentic code execution, so we can isolate and trust what an autonomous agent does, backed by monitoring and quality assurance