Design and develop a next-generation AI assistant for investigative teams. In this role, you'll lead the creation of Night Shift, a conversational interface that helps investigators uncover critical evidence through natural interactions. You'll own key components from the frontend chat experience to backend orchestration, ensuring seamless integration with data platforms and investigative tools.
What You'll Do
- Build and refine the conversational UI, crafting intuitive chat experiences that manage complex context and multi-step workflows
- Develop the backend systems that coordinate LLM interactions, including tool calling, function routing, and streaming responses
- Design and implement integrations between AI components and existing data platforms using REST, SSE, and WebSockets
- Collaborate with machine learning engineers to refine prompt strategies, evaluate model performance, and integrate agentic behaviors
- Define APIs and data contracts in partnership with platform teams to ensure reliable, secure access to investigative data
- Implement observability into AI workflows with structured logging, tracing, and metrics collection
- Work directly with investigators to understand real-world use cases and translate feedback into technical improvements
- Own end-to-end features, from interface design to backend services and data pipelines
- Establish testing strategies and quality standards for evolving AI capabilities
- Mentor team members on full-stack development and LLM integration patterns
What We're Looking For
- Strong proficiency in TypeScript, Node.js, and Express for building scalable web services and APIs
- Experience with React and modern frontend frameworks, especially for interactive chat interfaces
- Hands-on work with LLMs including OpenAI, Anthropic, or Gemini—particularly around prompt engineering, streaming, and context management
- Familiarity with agentic architectures: function calling, tool use, and workflow orchestration
- Confidence working with PostgreSQL and writing complex queries for data retrieval
- Understanding of cloud infrastructure: Docker, Kubernetes, Helm, and AWS services such as S3, SQS, and API Gateway
- Ability to navigate ambiguity and drive technical direction based on user needs and product goals
- A product-focused mindset—able to balance innovation with reliability in high-stakes environments
Preferred Experience
- Experience with LLM evaluation platforms like LangSmith or Langfuse
- Working knowledge of vector search and retrieval-augmented generation (RAG)
- Familiarity with microservices design and infrastructure as code (Terraform)
Benefits
- Flexible paid time off and 11 company-recognized holidays
- Full health coverage including medical, dental, and vision, with HSA contribution matching
- 12 weeks of fully paid parental leave; birthing parents receive additional recovery time
- Financial support for family planning—up to $50,000 lifetime benefit for adoption, surrogacy, or fertility treatments
