Madhive is the leading independent and fully customizable operating system built to help local media professionals build profitable, differentiated, and efficient businesses. Madhive empowers sales teams to extend their reach into streaming and connects local advertisers with the communities they serve. Madhive’s platform provides the unique ability to reach local audiences at national scale, with premium supply partnerships and end-to-end tools for planning, targeting, and measuring full-funnel campaign outcomes. Powering campaigns for over 30,000 small and medium businesses per day, Madhive is driving the evolution of local media.
We are seeking an experienced Staff Engineer to join our Maverick AI team. The successful candidate will build dynamic, very low-latency data pipelines and innovate novel, concise, and high-performing architectural improvements. You will lead as we develop best practices and create stability and operational efficiency for our increasingly complex data and database systems.
In this role, you will be a pivotal figure in shaping our technical strategy and execution for Maverick AI. Our data drives the capability of our AI product. Collaboration with our product team and other technology leaders will be central to your responsibilities.
What you’ll do:
Drive design and architecture discussions for data infrastructure supporting multiple autonomous AI agents, building alignment on complex decisions around feature serving, dynamic data access patterns, and real-time ML feature serving.
Design, code, test, and release high-quality software for ML feature pipelines and real-time serving infrastructure, ensuring our AI agents can access features with sub-millisecond latency across 100+ models.
Run and measure live experiments to optimize data delivery for unpredictable agent behavior patterns, testing hypotheses about caching strategies, pre-fetching, and adaptive pipeline architectures.
Collaborate with cross-functional teams including AI researchers and ML engineers to understand how different agents generate research requests and design data solutions that scale with their evolving needs.
Apply your engineering expertise to solve challenges unique to serving large volumes of data to agentic systems, such as handling sudden request spikes when multiple agents converge on similar research areas or managing feature freshness for real-time model inference.
Support on-call assignments for critical AI serving infrastructure, ensuring feature pipelines maintain reliability even under unpredictable agent-generated loads.
Mentor junior engineers on the unique challenges of AI infrastructure, from feature engineering best practices to debugging data issues in multi-model serving environments, supporting hiring and evaluation of candidates.
Write technical documents to influence architectural decisions around our feature store design, agent data access patterns, and strategies for scaling to thousands of models.
7+ years’ experience working with big data systems that can process and transform data at petabyte scale.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
Experience working in a brisk-paced, high-ambiguity, high-innovation delivery environment.
Familiar with messaging systems, batch processing, serverless, and streaming technologies.
Understanding of both OLTP and OLAP database systems.
You are an engineer for whom the dataset size doesn’t matter. Your team’s services can return results with the same accuracy and latency, whether from a 1 GB or 10 PB dataset.
You’ve implemented multiple retrieval-augmented generation (RAG) systems and are intimately familiar with the trade-offs between different types of low-latency data retrieval systems.
Handled database design and considerations for data at scale for transaction management, reporting, and analytics.
You enjoy designing and implementing critical parts of complex systems, utilizing best-of-breed algorithms, design patterns, and system design skills.
Handled operational aspects of large-scale systems focusing on observability, tech debt management, code refactoring, and robust software development and release processes.
Articulate technically complex topics in an easy-to-understand way via written and verbal communication methods.
Our stack runs entirely on GCP. Our engineers are language agnostic, but core technologies for our backend include Golang, gRPC, BigQuery, Postgres, Airflow, Bigtable, Docker, Spanner, Firebase, Kubernetes, and Terraform.
The approximate compensation range for this position is $200,000-$275,000. The actual offer, reflecting the total compensation package and benefits, will be determined by a number of factors including the applicant's experience, knowledge, skills, and abilities, as well as internal equity among our team.
Madhive is a dynamic, diverse, innovative, and friendly place to work. We embrace our differences and believe they fuel our creativity. We come from varied backgrounds and think that’s important. Whether it’s taking ideas from previous lives and applying them in different ways or creating something completely new, we are all trail-blazing team players who think big and want to make an impact.
We are committed to cultivating a culture of inclusion and collaboration. We welcome diversity in education, culture, opinions, race, ethnicity, gender identity, veteran status, religion, disability, sexual orientation, and beliefs.
Please be advised that we will NOT be using third-party recruiting agencies for this search.
Originally posted on Himalayas
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