Job description

ABOUT OUTTAKE Outtake exists to empower and facilitate trust for a digital-first world. Today, impersonation, fraud, AI-driven scams, and identity abuse spread faster than any security team can respond to. So we built something different: an agentic AI platform that proactively detects, monitors, and takes down impersonators, automating protection in hours, not weeks. Built by ex-Palantir, ex-CTO/founders, and ex-Notion engineers, Outtake is designed for clarity, autonomy, and velocity. Our goal is ambitious: become the trust layer of the modern internet. And we intend to do it with a lean, dense, exceptionally talented team. Outtake is backed by top-tier investors and operators who believe in our mission and our model. With strong financial footing and a long runway, we prioritize creating an environment where people can do the best work of their careers. THE ROLE This is a staff-level infrastructure generalist role. You will set the technical direction of Outtake’s infrastructure and build the systems that support our next orders of magnitude of growth. The role begins as an individual contributor position; experience growing and leading infrastructure teams will be valuable as the function scales. Outtake needs to search, process, and investigate billions of pieces of content quickly. You will own the foundations that determine how this data is stored, indexed, retrieved, and moved; how asynchronous work is scheduled and executed; and how our systems use cloud compute, storage, and networking. This is a software engineering role. You will design and build production infrastructure systems, expose them through clear internal interfaces and abstractions, and lead the migrations required to adopt them. WHAT YOU’LL DO - Set the technical direction for Outtake’s infrastructure across databases, search and retrieval, data processing, asynchronous execution, and cloud architecture - Redesign our search and retrieval systems to support fast investigation across billions of pieces of content - Evolve our relational database architecture through sharding, partitioning, indexing, caching, and new data-access patterns - Own the application and infrastructure changes required to migrate live systems safely, including changes to service topology and deployment strategy - Design and build scalable asynchronous systems for scheduling, queues, workflows, retries, backpressure, rate limiting, and failure recovery - Build data infrastructure for high-volume ingestion, streaming, batch processing, enrichment, and reprocessing - Develop shared infrastructure services, APIs, libraries, and primitives that product engineers can use without needing to understand the underlying implementation - Own the cloud foundations required by these systems, including compute, storage, networking, isolation, resource management, and deployment architecture - Evaluate build-versus-buy decisions and make tradeoffs across latency, throughput, consistency, durability, cost, and complexity - Work across engineering teams to identify repeated infrastructure problems and turn them into reusable systems - Operate the systems you build, use production evidence to improve their architecture, and automate recurring operational work - Write technical proposals, establish architectural standards, and guide other engineers through complex systems decisions - As the infrastructure foundation matures, we expect to grow this into a broader infrastructure team with dedicated ownership across data systems, cloud infrastructure, and developer platforms WHAT WE’RE LOOKING FOR - Experience operating at staff scope: identifying important technical problems, setting direction across team boundaries, and leading complex projects from design through adoption - A track record of designing and building distributed infrastructure systems used by other engineers or products - Experience scaling production systems through significant increases in data volume, traffic, or workload complexity - Deep knowledge of relational database architecture, including data modeling, access patterns, indexing, partitioning, sharding, caching, and migration - Experience building or evolving high-throughput asynchronous systems, with a strong understanding of scheduling, ordering, retries, idempotency, backpressure, and partial failure - Experience with large-scale search and retrieval systems, including the tradeoffs among lexical search, vector retrieval, indexing speed, freshness, relevance, and cost - Experience building ingestion, streaming, or batch-processing systems for large data volumes - Work across the underlying cloud infrastructure when changes to compute, storage, networking, or deployment architecture are required to scale our data systems LIFE AT OUTTAKE - Office: For those in NY, we are an in-person team (5 days a week, with flexibility as needed) working out of a stunning waterfront office in Brooklyn. Collaboration, speed, and clarity matter. - Health: 100% company-paid medical, dental, and vision for employees. - Time Away: Flexible PTO. We trust adults to manage energy, not clock time. - Culture & Team: Annual company retreats and regular in-person events. Outtake is an equal opportunity employer. We are committed to building a diverse, inclusive team.

Requirements

Must-haves

This is a software engineering role. You will design and build production infrastructure systems, expose them through clear internal interfaces and abstractions, and lead the migrations required to adopt them.
Set the technical direction for Outtake’s infrastructure across databases, search and retrieval, data processing, asynchronous execution, and cloud architecture
Redesign our search and retrieval systems to support fast investigation across billions of pieces of content
Evolve our relational database architecture through sharding, partitioning, indexing, caching, and new data-access patterns
Own the application and infrastructure changes required to migrate live systems safely, including changes to service topology and deployment strategy
Design and build scalable asynchronous systems for scheduling, queues, workflows, retries, backpressure, rate limiting, and failure recovery
Build data infrastructure for high-volume ingestion, streaming, batch processing, enrichment, and reprocessing
Develop shared infrastructure services, APIs, libraries, and primitives that product engineers can use without needing to understand the underlying implementation
Own the cloud foundations required by these systems, including compute, storage, networking, isolation, resource management, and deployment architecture
Evaluate build-versus-buy decisions and make tradeoffs across latency, throughput, consistency, durability, cost, and complexity
Work across engineering teams to identify repeated infrastructure problems and turn them into reusable systems
Operate the systems you build, use production evidence to improve their architecture, and automate recurring operational work
Write technical proposals, establish architectural standards, and guide other engineers through complex systems decisions
As the infrastructure foundation matures, we expect to grow this into a broader infrastructure team with dedicated ownership across data systems, cloud infrastructure, and developer platforms
Experience operating at staff scope: identifying important technical problems, setting direction across team boundaries, and leading complex projects from design through adoption
A track record of designing and building distributed infrastructure systems used by other engineers or products
Experience scaling production systems through significant increases in data volume, traffic, or workload complexity
Deep knowledge of relational database architecture, including data modeling, access patterns, indexing, partitioning, sharding, caching, and migration
Experience building or evolving high-throughput asynchronous systems, with a strong understanding of scheduling, ordering, retries, idempotency, backpressure, and partial failure
Experience with large-scale search and retrieval systems, including the tradeoffs among lexical search, vector retrieval, indexing speed, freshness, relevance, and cost
Experience building ingestion, streaming, or batch-processing systems for large data volumes
Work across the underlying cloud infrastructure when changes to compute, storage, networking, or deployment architecture are required to scale our data systems

Nice-to-haves

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Keywords to mirror

Platform: ashby
Effort: quick

Benefits

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Dental

Vision

Pto