We are seeking 4 AI & LLM Engineer (part-time 80 hours to full-time) to design, build, and operate production-grade AI systems.

For applicants seeking internship: 2 additional spots available - indicate clearly your areas of expertise and further development.

When successful, you will report to the AI & LLM Team Lead based in Germany and be part of a team of 3.

This role focuses on LLM-powered applications, MLOps, and AI server / MCP (Model Context Protocol) infrastructure to deliver reliable, safe, and scalable AI experiences.

Remote or hybrid (Singapore, Estonia, Poland or Germany).

Entire organisation meets weekly on Tuesday 9pm-10pm Singapore which you must be able to attend, and team has a regular standup 3x a week.

Key Responsibilities

• Design and implement LLM-powered services
  • Build and maintain back-end services that integrate one or more LLM providers (e.g. OpenAI, Anthropic, open-source models).
  • Develop prompt orchestration, retrieval-augmented generation (RAG), tools, and agents for real user-facing workflows.
  • Implement evaluation and monitoring loops to improve response quality over time.
• MLOps & productionisation
  • Set up or extend MLOps pipelines for model training, fine-tuning, evaluation, and deployment (CI/CD for models and prompts).
  • Automate data pipelines for logging, cleaning, labeling, and feedback ingestion.
  • Implement experiment tracking and versioning for models, datasets, and prompts.
• AI servers / MCP infrastructure
  • Design and build AI server or MCP-compliant services that expose tools, data sources, and workflows to LLMs in a secure, observable way.
  • Implement robust authentication, rate limiting, and observability (tracing, metrics, logging) for AI endpoints.
  • Optimise performance and cost (throughput, latency, caching, batching, token usage, and model selection strategies).
• Reliability, safety, and quality
  • Implement guardrails for safety, privacy, and compliance (content filters, PII handling, policy enforcement).
  • Define and track quality metrics for AI features (task success, latency, user satisfaction, hallucination rate).
  • Collaborate with product and design to translate real user needs into robust AI behaviors.
• Cross-functional collaboration
  • You have an apt for research and curiosity that drives your work. You enjoy sharing what you’ve learned and discovered including failures or hiccups.
  • Naturally share regular progress updates and use Jira and similar tools.
  • Work closely with product, design, and other engineers to scope projects, define milestones, and ship iteratively.
  • Write clear technical documentation for services, APIs, and data flows.
  • Contribute to engineering best practices around code quality, testing, and reviews.

Must-Have Experience

• LLM & AI systems
  • Hands-on experience building and shipping LLM-powered features or applications.
  • Strong proficiency in Python (and/or TypeScript/Node) for back-end and AI workflows.
  • Familiarity with at least one major LLM ecosystem (e.g. OpenAI, Anthropic, Azure OpenAI, open-source LLMs like Llama or Mistral).
• MLOps
  • Experience setting up or working with MLOps pipelines (e.g. using tools like MLflow, Weights & Biases, Vertex AI, SageMaker, or similar).
  • Experience with deploying and monitoring models in production (APIs, batch jobs, or streaming).
  • Comfort with containerisation and deployment (Docker, Kubernetes, or serverless platforms).
• AI Servers / MCP
  • Experience implementing AI-serving infrastructure such as custom inference servers, gateways, or orchestration layers.
  • Exposure to Model Context Protocol (MCP) or similar patterns (tool servers, function calling, or plugin infrastructures).
  • Ability to design clean, well-documented APIs for AI tools and integrations.
• Core engineering skills
  • Strong understanding of distributed systems basics (latency, reliability, scalability, observability).
  • Solid software engineering fundamentals: testing, code review, debugging, and performance tuning.
  • Experience working in cloud environments (GCP preferred).

About You: