Software Engineer - Data Platform

About Us

At MAI (pronounced “my”), we're on a mission to democratize advanced advertising technology. We believe that cutting‑edge marketing tools, once exclusive to large enterprises with massive budgets, should be accessible to everyone. Our platform uses AI agents to automate and optimize performance marketing, empowering small and mid‑sized businesses to scale their ad spend profitably without the need for an agency or endless hours of manual campaign management.

Founded by ad platform veterans from Google and Instacart, we've successfully raised a $25 million Seed funding round led by Kleiner Perkins to accelerate our growth. This capital will be used to expand our product and engineering teams, bringing our vision of intelligent, autonomous marketing to life. Our AI agents have already proven their value, helping clients drive 40% more sales and managing millions in monthly Google Ads spend.

Our client waitlist is growing by the day.

While traditional software has a clear playbook, building the infrastructure for autonomous, intelligent agents is a new frontier—and we're writing the manual.

As an early Software Engineer at MAI, you won't just be writing code; you'll be the architect of the entire ecosystem where our AI agents live, learn, and operate. You will have a profound impact across our entire stack
, from the foundational data platforms that feed our agents, to the core agentic frameworks that allow them to reason, to the scalable serving systems that deliver their intelligence to our customers. This is a rare opportunity to build a truly AI‑native product from the ground up and solve problems at the forefront of the industry.

You won't just be a cog in a large machine.
You'll be an athlete on a small, focused team of fewer than ten engineers, with immense impact and the ability to shape the future of our company. We're in the early days of forming three core teams:

• Product Engineering & Infrastructure
• AI Platform & Foundation
• Agent Application & Quality

You’ll have the unique chance to learn and grow your skillset as these teams evolve. We encourage you to lean on your specializations while taking on new projects you've never done before,
learning from your peers and becoming a more well‑rounded engineer.

• Own and evolve the company’s data platform, covering both batch and streaming pipelines to ensure scalability, reliability, and performance.
• Design, implement, and maintain robust ETL/ELT processes to integrate data from diverse sources, including marketing and advertising platforms (e.g., Google Ads, Meta Ads, Amazon Ads).
• Define and standardize core data models, base tables, and schemas to ensure consistency, usability, and accuracy across analytics and ML applications.
• Implement strong data governance, access control, and security practices to protect sensitive business and customer information.
• Optimize data storage, retrieval, and query performance across large‑scale datasets.
• Partner with ML engineers, marketing ops, and product teams to ensure data availability and quality for analytics, experimentation, and production use cases.
• Build and maintain real‑time data streaming infrastructure to power event‑driven systems and business insights.
• Develop monitoring, alerting, and validation frameworks to guarantee data accuracy and pipeline reliability.
• Contribute to documentation, knowledge sharing, and best practices for the data platform.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science or related fields.
• Strong experience with data pipelines (batch and/or streaming) using modern frameworks (e.g., Spark, Beam, Flink, Kafka, Pub/Sub).
• Proficiency with SQL and experience designing data schemas for analytical and operational use cases.
• Hands‑on experience with data warehouses and data lakes (e.g., Big Query, Snowflake, Redshift, or similar).
• Familiarity with integrating data from third‑party APIs and marketing/ad platforms.
• Strong programming skills in Python, Java, or Scala for data engineering workflows.
• Solid understanding of data security, compliance, and governance practices.
• Experience working with cloud platforms…