Senior Software Engineer

At Algolight, we live and breathe the future of artificial intelligence and the physical world.

🌍 Learn more about us: https://algolightltd.com

Our mission it two-folder:

On the civilian side, we build labeled 3D information layers from all types of sensors—for smart cities, drones, autonomous vehicles, infrastructure, public safety, and far beyond.
On the defense side, we bring true real-time intelligence to the edge—anywhere, for any sensor, at any point on the map—enabling smart, real-time decisions in the field.

Border Team Mission

At Algolight, we are building the next generation of autonomous, multi-sensor AI systems designed to operate in real, operational environments — not just in theory. Our work spans from raw sensor data to high-confidence triage, reasoning, and autonomous decision-making, enabling scalable, robust, and intelligent systems that reduce cognitive load on operators and help drive safer, more effective national operations.

As part of a national effort to modernize border operations, you will be a core technical force — helping define, design, implement, and scale AI-driven architectures that tie together data, models, agents, and operational systems.

As a Senior Software Engineer – Data-Centric AI & Systems, you will build and own the core software infrastructure that connects sensors, data platforms, AI models, and operational systems.

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🚀 What You’ll Be Responsible For

Core Backend & Data Systems Development

• Design and implement high-performance backend services for ingesting, transforming, and routing sensor data.
• Build software that supports:
  • real-time streaming pipelines
  • near-real-time inference
  • offline data processing and training workflows

Streaming, Messaging & Data Movement

• Implement and maintain data pipelines using:
  • message brokers (Kafka / Redpanda / RabbitMQ / ZeroMQ)
  • stream processing frameworks (Flink, Spark Streaming, custom async pipelines)
• Handle backpressure, ordering, fault tolerance, and replayability.

AI Pipeline Integration

• Build software layers that interface with:
  • deep learning inference services
  • perception and tracking pipelines
  • agentic / LLM-based systems
• Integrate with model serving stacks:
  • Triton Inference Server
  • custom PyTorch / TensorRT services

Storage & Data Management

• Work with multiple storage paradigms:
  • object storage (S3-compatible, MinIO)
  • relational databases (PostgreSQL)
  • NoSQL / time-series databases
  • vector databases (FAISS, Milvus, Weaviate)
• Design schemas, partitioning strategies, and retention policies.

Performance, Reliability & Observability

• Optimize systems for:
  • low latency
  • high throughput
  • predictable memory usage
• Implement observability:
  • structured logging
  • metrics 
  • tracing
• Debug production issues using real sensor data.

Deployment & Operational Readiness

• Deploy and operate systems on:
  • on-prem GPU servers
  • hybrid cloud environments
• Work with containers (Docker) and orchestration (Kubernetes when applicable).
• Support shadow-mode deployments and field trials.

🔎 Systems & Sensors You’ll Work With

• Video streams: VIS, NIR, SWIR, MWIR, LWIR
• Radar and SAR systems
• Event-based cameras
• Acoustic, seismic, fiber, and vibration sensors
• AI pipelines for perception, fusion, and autonomy

🎯 What We Are Looking For

Required Experience

• 5+ years as a software engineer working on backend, systems, or data-intensive platforms.
• Strong experience with Python in production systems.
• Experience with at least one systems language: C++ / Go / Rust.
• Proven experience building distributed or real-time systems.

Core Technical Skills

• Languages:
  Python, C++ / Go / Rust
• Data & Streaming:
  Kafka / Redpanda / RabbitMQ, async pipelines, stream processing
• Databases & Storage:
  PostgreSQL, NoSQL stores, object storage, vector databases
• AI Systems:
  PyTorch, TensorRT, Triton Inference Server (integration-level, not research-only)
• Infrastructure:
  Docker, Linux, CI/CD pipelines
• Observability:
  Prometheus, Grafana, OpenTelemetry, structured logging

⭐ Strong Advantages

• Experience with sensor data (video, radar, signals).
• Hands-on work with ML pipelines or MLOps (training, inference, monitoring).
• Experience deploying AI systems to edge or constrained environments.
• Background in autonomy, robotics, defense, or mission-critical systems.
• Experience supporting AI researchers and training teams.

🌟 What Awaits You at Algolight

• Ownership of core runtime software powering national-scale AI systems.
• Real-world constraints that force clean, disciplined engineering.
• Daily work at the intersection of:
  data systems × AI × real sensors.
• Close collaboration with architects, perception leads, radar experts, and researchers.

A culture that values engineering depth over buzzwords.