Software Engineer, Delivery

About Troveo

Troveo is building the next-generation data platform to train AI video models. We offer the world’s largest library of AI video training data—featuring millions of hours of licensed video content. Our end-to-end data pipeline connects creators, rights holders, and AI research labs, enabling scalable, compliant, and innovative uses of video for AI applications and model development.

We are an early-stage, high-growth venture backed by forward-thinking investors, and we’re seeking a deeply technical engineer to help build and optimize the backbone of our content delivery systems.

As a Software Engineer, Delivery
, you’ll own the reliability, performance, and scalability of Troveo’s video content delivery infrastructure. This role is highly hands-on, blending systems engineering with data-centric development to ensure seamless transfer and processing of petabyte-scale video data.

You’ll work across data transport, distributed processing, and client integration layers - building efficient, fault-tolerant systems that power Troveo’s end-to-end AI data pipeline. Ideal candidates have a strong command of algorithms, concurrency, and network programming, paired with a pragmatic mindset for maintaining production-grade reliability.

Core Delivery Engineering

• Design, build, and maintain robust delivery pipelines that handle large-scale video ingestion, transformation, and distribution across distributed systems.

• Optimize throughput, latency, and fault-tolerance across Troveo’s global data delivery layer.

• Implement monitoring, redundancy, and recovery mechanisms to maintain system reliability at scale.

• Collaborate with platform and ML teams to ensure smooth data handoffs into analytics, training, and indexing workflows.

Systems Design & Optimization

• Apply strong fundamentals in algorithms, data structures, and concurrency to optimize data movement and task scheduling.

• Develop and tune software for high-performance, parallel data processing and low-latency streaming workloads.

• Implement and optimize both OLAP and OLTP integrations—bridging analytics warehouses and transactional databases for real-time delivery insights.

• Leverage tools like Python
  , Go
  , or Node.js to build efficient services and automation frameworks.

Network & Distributed Systems

• Build and maintain network-aware systems that support high-throughput video delivery using TCP/UDP, socket programming, and custom streaming protocols.

• Profile, benchmark, and optimize data transmission across multi-region infrastructure.

• Contribute to distributed coordination mechanisms to ensure system consistency and efficient data replication.

Reliability & Maintenance

• Own production operations for delivery services—implement alerting, observability, and incident response workflows.

• Partner with infrastructure engineers to scale compute and storage resources dynamically.

• Drive continuous improvement in uptime, throughput, and cost efficiency.

• 4 - 6 years of experience in software engineering, with focus areas in distributed systems, networking, or data infrastructure.

• Deep understanding of algorithms
  , data structures
  , and concurrency control
  .

• Proven experience building systems that interact with both OLAP (e.g., Snowflake, Big Query, Redshift) and OLTP (e.g., Postgres, MySQL, Dynamo
  
  DB) layers.

• Strong proficiency in Python
  , Go
  , or Node.js for systems-level development.

• Familiarity with network programming principles
  —including TCP/UDP protocols, sockets, and performance optimization for high-throughput data streams.

• Experience operating within distributed, data-heavy production environments.

• Clear, pragmatic communication skills; capable of collaborating closely with data, ML, and platform teams.

• Experience designing and implementing microservices architectures
  .

• Familiarity with vector databases
  , Elasticsearch
  , or similar search/indexing technologies.

• Exposure to modern streaming frameworks or distributed task queues (e.g., Kafka, Celery, Airflow).

• Knowledge of cloud infrastructure operations (AWS preferred).

Location: Strong preference for candidates based in the San Francisco Bay Area
.

Compensation: $120,000 – $160,000 base salary + meaningful equity participation.

• Work at the cutting edge of AI, video, and distributed data infrastructure.

• Build the systems that deliver and power the world’s largest AI video datasets.

• Collaborate with a world-class team of engineers, researchers, and industry experts.

• High autonomy, high impact—your work will directly shape Troveo’s core delivery platform.

• Competitive compensation with significant equity upside.