Senior Software Engineer, Intelligence

Flock Safety Flock Safety · Enterprise · United States · Remote · Engineering

Senior Software Engineer focused on building backend systems for an investigative platform, specifically designing and deploying orchestration backends for LLM tool-calling, function execution, and multi-step reasoning workflows. The role involves engineering integration pipelines and bridging LLM outputs with internal APIs, emphasizing production-grade, low-latency infrastructure.

What you'd actually do

  1. Lead the architectural evolution and backend execution for Flock's investigative workflows.
  2. Design and deploy high-performance orchestration backends that manage complex LLM tool-calling, function execution, and multi-step reasoning workflows.
  3. Engineer high-throughput integration pipelines and secure connectors linking conversational interfaces directly to core data platform microservices.
  4. Partner with Machine Learning and Data Engineering teams to bridge unstructured LLM outputs with structured internal APIs, maintaining strict schema validation and error handling.

Skills

Required

  • performant production code in Python or TypeScript
  • scalable backend web services and microservices
  • PostgreSQL, OLAP databases, and Redis
  • agentic workflows, function calling, Model Context Protocol tools, and prompt engineering
  • cloud-native infrastructure, AWS, Kubernetes, Docker, and CI/CD pipelines
  • taking ambiguous technical problems in zero-to-one product spaces and translating them into clear architectural roadmaps

Nice to have

  • LLM evaluation frameworks
  • vector search
  • infrastructure-as-code

What the JD emphasized

  • design and deploy high-performance orchestration backends
  • manage complex LLM tool-calling, function execution, and multi-step reasoning workflows
  • engineer high-throughput integration pipelines
  • bridge unstructured LLM outputs with structured internal APIs
  • production-grade, low-latency infrastructure

Other signals

  • design and deploy high-performance orchestration backends
  • manage complex LLM tool-calling, function execution, and multi-step reasoning workflows
  • engineer high-throughput integration pipelines
  • bridge unstructured LLM outputs with structured internal APIs