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.

We’re a high-performance, low-ego team driven by urgency, collaboration, and bold thinking. Working at Flock means tackling big challenges, moving fast, and continuously improving. It’s intense but deeply rewarding for those who want to make an impact.

With nearly $700M in venture funding and a $7.5B valuation, we’re scaling intentionally and seeking top talent to help build the impossible. If you value teamwork, ownership, and solving tough problems, Flock could be the place for you.

The Opportunity

We're hiring a 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. You'll 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. If you've built LLM-powered products and thrive at the intersection of customer impact and technical depth, this role is for you.

The 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)

• Product-minded: translate user feedback into technical requirements and make pragmatic tradeoffs

• Bonus points for: LLM evaluation tools (LangSmith, Langfuse), vector search/RAG, microservices architecture, or Terraform

90 Days at Flock

The First 30 Days:

• Onboard and Integrate:

  • Familiarize yourself with Flock's mission, investigative workflows, and how customers use our platform today

  • Pair with engineers across Cloud Software and ML teams to understand existing APIs, data models, and system architecture

  • Build relationships with key stakeholders to understand their capabilities and constraints. Meet with members of:

    • Machine Learning (agentic systems, model serving)

    • Data Engineering (investigative datasets, pipelines)

    • Platform teams (APIs, infrastructure)

    • Product and Design (customer needs, UX direction)

• Ship Early and Learn:

  • Complete a first-day push to production

  • Pick up initial sprint tickets: bug fixes, small UX improvements, or API integrations

  • Participate in customer feedback sessions to understand investigator workflows and pain points

The First 60 Days:

• Build the Foundation:

  • Deliver core conversational UI components and establish patterns for chat interfaces

  • Implement backend orchestration for LLM interactions and