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San Francisco, California, United States
Onsite
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 Fox, Notion, Perplexity, Vercel, and Brex 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.
As a Data Engineer at Serval, you'll be our first dedicated data hire, which means you'll own the entire data stack from day one and build the data function that serves the whole business. Right now our data lives across many systems for many teams: in-product, CRM, marketing, billing, support, finance, and more. Your first job is to consolidate all of it into a single, well-modeled warehouse the company can actually use, then build the pipelines, models, and self-serve layer that make that data trustworthy and accessible to every team. You will be a close partner with business and product stakeholders to identify and define the gold-standard metrics for the business, and be responsible for building the underlying systems to track them at high scale.
You'll set the patterns, choose the tools, and make the build-versus-buy calls that hold as we scale. You'll work closely with Engineering, Product, and our go-to-market and operations teams to make sure the data infrastructure serves both internal decision-making and the product itself. Beyond building the infrastructure, you'll be a critical partner to the business, working to understand what teams are really asking and delivering the answers that move them in the right direction.
Stand up our first unified data warehouse and own it end to end: modeling, pipelines, data quality, and performance, treating it like a product the whole company can rely on.
Partner with teams across the business to turn ambiguous questions into clear requirements and metrics the whole company aligns on.
Consolidate data from our production Postgres databases and SaaS systems (product usage, CRM, marketing, billing, support, finance) into a single source of truth, and push clean data back into the tools teams work in.
Design clean, performant data models with clear lineage, standardized nomenclature, and well maintained documentation to support self-serve BI.
Build internal data tools with applied AI, using Serval's own agents to turn recurring data questions into self-serve answers.
Own data quality, governance, and security from day one, so it's built in rather than bolted on later.
Make the vendor, tooling, and architecture calls for the data stack, keeping it lean and cost-aware.
Define the data engineering practices and standards the future team will build on.
5+ years of experience in data engineering and business analytics, with hands-on experience building and maintaining data warehouses and pipelines.
Expert SQL, including hands-on experience with PostgreSQL, and strong Python for pipeline development, scripting, and tooling.
Experience standing up a modern data warehouse or lakehouse from scratch (Snowflake, Databricks, or comparable) and building the ETL/ELT pipelines transform data into usable production databases using a modern stack (e.g.m Fivetran, DBT).
Hands-on experience with AWS and infrastructure as code (Terraform) for managing cloud data infrastructure.
Track record of owning data projects end to end and exercising sound judgment independently, ideally as an early or first data hire.
Strong product intuition and business curiosity: you can translate business questions into clean, usable data models, know what's worth measuring, and collaborate with a wide variety of technical & non-technical stakeholders.
Comfortable with the pace and ambiguity of a fast-growing startup environment.
Experience building internal data tools or agents with LLMs.
Familiarity with modern data-stack tooling for orchestration, transformation, and streaming.
Familiarity with our stack: Go, gRPC, React, TypeScript, Kubernetes, AWS, and Terraform.
Experience setting up self-serve analytics layers.
Early-stage startup experience or a track record of zero-to-one development.
Degree in Computer Science or a related engineering field.
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.