We are hiring an AI Platform Engineer in Singapore to help build a new agentic AI investigations platform for law enforcement and intelligence teams.
The platform will help investigators process large volumes of data, classify content, extract entities, connect evidence, and interact with investigative data through AI-assisted workflows, autonomous agents, and conversational interfaces. This is a hands-on engineering role for a strong platform engineer who can also deliver full-stack product features. This is not a research or prompt-engineering role. We are looking for an engineer who can design and build reliable systems that use AI in high-stakes investigative environments.
What You’ll Do:
- Implement production-grade agentic workflows, including tool use, routing, task orchestration, RAG, investigation chat, evidence summarization, and human-in-the-loop flows.
- Build integrations between LLMs, specialized models, embeddings, vector search, PostgreSQL, Temporal workflows, and internal investigative systems.
- Design and build backend services, APIs, data-processing workflows, and AI orchestration layers for the Link platform.
- Develop data ingestion, parsing, enrichment, and classification pipelines for structured and unstructured investigative data.
- Deliver end-to-end product features across backend and frontend using modern full-stack tooling and AI-assisted development workflows.
- Collaborate directly with customer-facing teams and selected customers in Singapore and across APAC to understand operational needs and translate them into product capabilities.
- Help define engineering standards, architecture patterns, and technical direction for a new strategic product line.
Requirements
What We’re Looking For:
- 5+ years of professional software engineering experience, with strong backend or platform engineering expertise.
- Strong experience with .NET/C#, Python, Java, Go, or similar backend languages.
- Experience building production-grade APIs, services, distributed systems, and asynchronous data-processing workflows.
- Practical experience with AI/ML systems, LLM APIs, inference engines such as llama.cpp or vLLM, open-source models, embeddings, RAG, agentic workflows, or conversational AI.
- Strong understanding of system design, scalability, reliability, observability, data structures, and algorithms.
- Experience with workflow orchestration, durable execution, background jobs, or distributed task processing. Temporal experience is a strong advantage.
- Ability to deliver full-stack features using modern frontend frameworks such as React and TypeScript.
- Experience using AI-assisted software development tools effectively in real engineering workflows. Terminal-native tools such as Claude Code are a strong advantage.
- Experience building and deploying software on AWS, GCP, or Azure.
- Comfort working with on-premise and offline environments.
- Strong ownership mindset and ability to operate in ambiguous environments.
- Ability to communicate clearly with engineering, product, customer-facing teams, and technical users in the field.
Strong Plus:
- Experience deploying AI capabilities in secure, air-gapped, offline, on-premise, or regulated environments.
- Experience with Temporal.
- Experience with React and TypeScript.
- Experience with media classification, computer vision, OCR, face or object detection, speech-to-text, or multimodal AI.
- Experience with law enforcement, intelligence, digital forensics, cybersecurity, fraud, compliance, OSINT, or investigation platforms.
- Experience with vector databases, embeddings, HNSW, semantic retrieval, or graph and link-analysis systems.
- Experience designing agentic systems with tool calling, memory, routing, guardrails, evaluations, and human approval flows.
- Experience with Docker, Kubernetes, AWS CDK, Terraform, CI/CD, observability, and production operations.
Why Join:
- Work on a new strategic AI product inside the company.
- Build technology used by law enforcement and intelligence teams to process complex investigative data.
- Work closely with real customers and real operational problems, rather than abstract demos.
- Help shape the architecture, product direction, and engineering culture of Link from an early stage.
- Join a small, high-impact team where strong engineers have meaningful ownership.