Job Description
### Who is Flock?
Flock Safety is the leading safety technology platform, helping communities thrive by taking a proactive approach to crime prevention and security. Our hardware and software suite connects cities, law enforcement, businesses, schools, and neighborhoods in a nationwide public-private safety network. Trusted by over 5,000 communities, 4,500 law enforcement agencies, and 1,000 businesses, Flock delivers real-time intelligence while prioritizing privacy and responsible innovation.
### The Opportunity
We're hiring a **Senior Software Engineer** to build **Night Shift**, a conversational AI assistant that helps investigators surface critical evidence and close cases faster. You'll design and implement the conversational interface, build the orchestration backend that manages LLM interactions and tool calling, and develop integration pipelines connecting our AI to Flock's existing data platform and APIs. This is a ground-floor opportunity where product thinking matters as much as technical execution: you'll shape chat experiences with complex context management, partner with platform teams to design new APIs or leverage existing ones, and solve the reliability challenges of deploying AI in high-stakes investigative workflows.
### Responsibilities
- Collaborate closely with ML engineers on prompt engineering and agentic workflows while maintaining a strong point of view on what makes a great user experience.
- Build LLM-powered products and thrive at the intersection of customer impact and technical depth.
### Skillset
- Love for coding and continuous learning, especially in the rapidly evolving LLM space.
- Resourceful problem-solver mindset: excel in ambiguous situations and take initiative to define product direction.
- Strong TypeScript / Node / Express skills for web services and API design (REST, SSE, WebSockets for streaming).
- Modern web framework expertise (React / TypeScript preferred), particularly for conversational UI and chat interfaces.
- Hands-on LLM experience: OpenAI/Anthropic/Gemini APIs, prompt engineering, streaming responses, and conversation context management.
- Familiarity with agentic patterns: function calling, tool use (MCP), and orchestrating multi-step workflows.
- API integration skills: consume existing APIs or design new ones to ground AI in investigative data.
- Database confidence: PostgreSQL and sophisticated SQL for data retrieval.
- Cloud infrastructure basics: Docker, Kubernetes (Helm), AWS services (S3, SQS, API Gateway).