Applied AI Engineer
Who We Are
Serval is an AI-native automation platform transforming how enterprises operate. We build intelligent agents that understand real-world workflows and execute them end-to-end — replacing manual processes and rigid legacy systems with adaptive, learning software. Founded in early 2024, Serval is already trusted by companies like General Motors, Notion, Perplexity, Vercel, Mercor, LangChain, and Verkada to automate high-volume, high-friction operational work across their organizations.
At the core of Serval is an agentic AI platform that turns natural language into production-grade workflows. Our agents don’t just respond to requests — they reason, take action across systems, and continuously improve with usage. What began with operational use cases has quickly evolved into a horizontal AI automation layer used across IT, HR, Finance, Security, Legal, and Engineering.
Our mission is to eliminate repetitive, manual work across the enterprise and give teams leverage through intelligent automation. Long term, we’re building the universal AI operations layer — a system of agents that sits across business functions and runs the workflows that keep modern companies moving.
We’re backed by leading investors including Sequoia Capital, Redpoint Ventures, Meritech, First Round, General Catalyst, Elad Gil, and others, and founded by product and engineering leaders from Verkada.
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.
What You'll Do
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.
What You'll Need
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.