Job description

About Us: At Reevo, we're reimagining the entire revenue stack from the ground up, and we're doing it with speed. We're building software that orchestrates every go-to-market motion, enabling B2B teams to operate faster, smarter, and more collaboratively. By combining automation, intelligence, and a radically intuitive interface, we're helping companies unlock new levels of productivity and growth across marketing, sales, ops, and customer success teams. If you're excited about working on a product that reshapes how revenue teams work and being surrounded by curious, driven teammates, you'll feel right at home here. From day one, you'll get real ownership, real mentorship, and real impact. Our team of 100+ builders has 30 exits under their belt, so you'll be in good company, and working alongside the best! About the Role: 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 What You Bring: - 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 What we offer: - Compensation: A highly competitive base salary and bonus structure, and early-stage equity that aligns your success directly with the company's growth. - Comprehensive benefits: health, dental, and vision coverage, generous paid time off (PTO), plus additional benefits that support how you work. - Growth and development: Career advancement paths, dedicated mentorship opportunities, and a strong commitment to investing in your continuous professional development and skill enhancement. - Dynamic culture: Join a collaborative, innovative, and fast-paced work environment where your direct contributions have a tangible and immediate impact on the product, the sales strategy, and the overall company trajectory. Here at Reevo, we know the best ideas come from people with different experiences and perspectives. We welcome candidates from all backgrounds and are proud to be an equal opportunity employer. We do not discriminate based on any protected characteristic, and we’re happy to provide accommodations throughout the application process.

Requirements

Must-haves

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
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
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

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

goaiml

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Paid Time Off

Professional Development