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# Software Engineer - Systems

- **Company:** Specter Incorporated
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Systems Engineering, C++ (Programming Language), Cloud Computing, Communications Protocols, Cyber Security, Network Congestion, Continuous Integration, Linux, Memory Management, Fault Tolerance, FFmpeg, H.264/MPEG-4 AVC, Hardware Design, Hardware Interface Design, Sensor Fusion, Wireless Sensor Networks, Software Engineering, Software Systems, Data Streaming, Transmission Control Protocol (TCP), Video Codec, Datadog, Cloud Platform System, Data Ingestion, High Efficiency Video Coding (HEVC), Concurrency, Parallel Computation, Build Management, Low Latency, Decoding
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/software-engineer-systems-san-francisco-ca--b572e4ec-f7f7-4b37-a7c6-1db16d165fd9

## About the Role

Software Engineering, Systems Engineering, Artificial Intelligence (AI) Agents, Materials Tracking, Computer Security, Wireless Communications, Robotics, Artificial Intelligence (AI), Systems Engineering, Cloud Computing, * Broad systems experience across the areas below, with demonstrable depth in at least one - whether that's networking, video/sensor pipelines, or low-level Linux systems work

 * Production Rust (preferred) or C++ in low-latency, embedded, or systems contexts - with real ownership of performance, reliability, and resource constraints
 * Deep networking knowledge (UDP, TCP, QUIC) beyond the API level - packet loss, flow control, retransmission, and tuning for real-world conditions; strong Linux systems fundamentals including IPC, scheduling, and memory management
 * Hands-on hardware integration experience - cameras, IMUs, or other sensors - including driver interfaces, kernel boundaries, and video pipelines (capture, encode/decode, streaming via V4L2, GStreamer, FFmpeg, or similar)
 * Proficiency with concurrency and parallel programming - lock-free structures, async runtimes, thread management - with a track record of shipping correct, performant, concurrent code
 * Comfortable owning CI infrastructure, test harnesses, benchmarking pipelines, and observability tooling alongside feature work

Nice to Have

 * Experience working alongside real-time, multimodal ML data ingestion systems - understanding the data quality, latency, and throughput requirements that make or break model performance
 * Hands-on experience with modern video codec implementations (H.264, H.265, AV1) across hardware platforms - encoder tuning, rate control, and platform-specific acceleration (V4L2, NVENC, etc.)
 * Robotics, perception, or state estimation background - familiarity with sensor fusion, localization, tracking algorithms
 * Experience writing Rust and Nix

## Description

Specter is hiring a Software Systems Engineer to build the real-time device software at the heart of our platform - spanning sensor integration, video pipelines, low-latency networking, and the infrastructure that ties it all together. This role owns the full stack from hardware interface to cloud edge, working closely with ML, perception, and platform teams to ship the performant, reliable systems that power autonomous monitoring across our customers' physical environments., * Design and build low-latency networking infrastructure connecting embedded devices and cloud systems - protocol design, congestion handling, and tuning for throughput and reliability across a distributed sensor network

 * Build resource-efficient pipelines to ingest and egress multimodal sensor data and telemetry, handling packetization, buffering, and backpressure across constrained device environments
 * Own low-latency command and control infrastructure across a distributed sensor network, with a focus on fault tolerance, deterministic timing, and graceful degradation
 * Integrate and fuse multimodal data streams from cameras, IMUs, and other sensors - working across driver boundaries, synchronization, and calibration to produce reliable inputs for downstream algorithms
 * Build and optimize video and image processing pipelines end-to-end: capture, hardware-accelerated encode/decode, streaming, and storage
 * Contribute to tracking and state estimation algorithms, bridging raw sensor data and meaningful system outputs in close collaboration with ML and perception teams
 * Build and maintain CI pipelines, test harnesses, and reliability tooling - the simulators and replay systems that let the team move fast without breaking things in the field
 * Instrument, profile and benchmark system performance - CPU/GPU utilization, memory pressure, network throughput and latency - and drive systematic improvements