Applied AI Engineer

Who We Are

At Serval, we're building the AI platform for IT teams. Our goal is to take on legacy players like ServiceNow, a $230+ bn company, by building the platform for AI agents to resolve IT issues instead of humans.

Serval “automates the automation,” using a natural language-to-code workflow builder and AI agents that discover and deliver automations for tedious IT workflows.

Our mission is to free IT departments from the #helpdesk channel by creating the simplest way to automate employee onboarding / offboarding, software access management, and the long tail of employee requests. Long term, our vision extends to developing a universal workflow automation platform for all business functions.

Serval was founded by product and engineering leaders from Verkada and is backed by industry-leading investors like First Round, General Catalyst, Alt Capital, and Box Group.

Role Overview

As an Applied AI Engineer at Serval, you’ll help build the intelligence behind our platform - the foundational AI agents that reason, act, and automate complex IT workflows. Your work will apply cutting-edge models and techniques in creative, real-world ways to convert repetitive IT processes into intelligent automation.

Key Responsibilities

Design, build, and deploy AI-powered features from the ground up.

Develop and optimize Serval’s applied AI systems — from model selection and fine-tuning to inference and evaluation pipelines.

Integrate AI capabilities into production environments, ensuring reliability, scalability, and performance.

Collaborate across engineering and product to bring new customer experiences to life.

Continuously evaluate model performance and improve results based on data and user feedback.

Help establish AI engineering best practices and raise the technical bar across the team.

Requirements

Experience as a software engineer or machine learning engineer with a focus on applied AI.

Proven experience developing and deploying production-grade AI systems, ideally leveraging large language models or foundation models.

Experience with prompt engineering, fine-tuning, or evaluation techniques for LLMs.

Comfort working with APIs, data pipelines, and cloud environments (AWS, GCP, or similar).

Deep appreciation for delivering high-quality user experiences, not just high-performing models.

Excellent communication skills and ability to thrive in a fast-paced, collaborative startup environment.

Degree in Computer Science or a related technical field.

Nice to Have

Experience building AI-native applications or tools that use LLMs in production.

Familiarity with our stack : Go, gRPC, React, TypeScript, Kubernetes, AWS, and Terraform.

Early-stage startup experience or a track record of zero-to-one product development.

Experience with retrieval-augmented generation (RAG), vector databases, or orchestration frameworks.

What We Offer

Impact : Be a key player in shaping the success of our product and company.

Growth : Build a fundamentally new AI product offering with the support of our experienced team and investors. Grow rapidly with the company.

Culture : Join a culture that values innovation, ownership, accountability, and fun.

Compensation : Competitive salary, equity and benefits.