Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.
We are seeking a Software Engineer to join our core engineering team in building high-throughput backend services and distributed platform infrastructure.
In this role, you will design and scale event-driven architectures, asynchronous workflows, data-intensive services handling complex, high-concurrency workloads and various internal data tools. You will tackle core challenges in system resilience, data consistency, fault tolerance, and performance optimization while owning services from technical design to production operations.
System Architecture & Development: Design, build, and maintain high-performance, fault-tolerant backend services and event-driven systems.
Distributed Workflows: Build robust processing pipelines capable of handling high-volume data streams and long-running operations.
API & Data Infrastructure: Implement low-latency APIs and integrate search and indexing capabilities across distributed data stores.
Operational Excellence: Optimize system throughput, reduce latency, and ensure reliability under failure scenarios, retries, and high concurrency.
Engineering Leadership: Participate in design reviews, set coding standards, drive technical planning, and mentor junior and mid-level engineers.
End-to-End Ownership: Lead projects through the complete software lifecycle, including technical specs, implementation, CI/CD, and production observability.
Experience: 7+ years of professional experience building and scaling production backend or platform systems.
Language Proficiency: Strong experience with at least one modern programming language.
Distributed Systems: Proven understanding of event-driven architecture, concurrency models, fault tolerance, and data consistency patterns.
Cloud & Infrastructure: Hands-on experience developing within cloud environments (AWS is a plus).
Modern AI Workflows: Demonstrated ability to leverage AI-assisted development tools (e.g., AI coding assistants, CLI agents) to accelerate development, testing, and debugging.
Engineering Fundamentals: Strong track record in automated testing, code reviews, technical documentation, and production troubleshooting.
Messaging & Streaming: Production experience configuring, tuning, and managing Apache Kafka or similar message brokers.
Data & Search: Experience with distributed/NoSQL databases and search engines such as Opensearch.
Containers & IaC: Hands-on experience with Kubernetes, Docker, and Infrastructure-as-Code (Terraform).
Observability: Experience with distributed tracing, APM tools, and real-time production monitoring.
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