Senior AI Platform Engineer

Overview

In this role you will help design and build the core AI platform powering 9fin’s AI-enabled debt markets products. You’ll shape architecture, set engineering standards, and create reusable infrastructure for AI, ML, and autonomous workflows. Working with backend and AI engineers, you’ll enable scalable, production‑grade AI capabilities—from RAG and embeddings to agentic AI and orchestrated data workflows. This is a ground‑up platform role with a strong impact on future product experiences and operational excellence.

Pay / Benefits

• Competitive Salary
• Equity
• Pension (4% employee with 7% company match)
• Private Medical Insurance
• 25 holiday days per year
• Hybrid working model

Responsibilities

• Design and evolve the enterprise AI platform powering AI products across 9fin
• Develop scalable AI services for Agentic AI, RAG, embeddings, vector search, model serving, and automation
• Build orchestration layers to transform structured and unstructured data into reusable AI capabilities
• Create production-ready AI applications using modern LLM frameworks and orchestration tools
• Design reusable platform components for prompts, model serving, vector search, embeddings, AI gateways, and evaluation services
• Build APIs, SDKs, and developer tooling for self-service AI development across teams
• Design secure, scalable deployment pipelines for AI models and applications
• Develop AI observability including monitoring, tracing, evaluation, cost optimisation, and production quality metrics
• Collaborate with AI/Backend engineers and leadership to define architecture and standards
• Establish best practices around testing, governance, Responsible AI, deployment, and operational excellence
• Continuously evaluate emerging AI technologies to evolve the platform

Key requirements

• 5+ years of software engineering experience
• 2+ years building AI/ML platforms, Generative AI, or production ML systems
• Hands-on experience with LLM-powered applications
• Experience with MCP and RAG, embeddings, vector databases, and modern LLM orchestration
• Backend experience with Python and/or TypeScript
• Design of scalable REST APIs and event-driven architectures
• Experience building reusable platform capabilities, SDKs or internal tooling
• Cloud-native development with Docker, Kubernetes, CI/CD, containerised deployment
• Experience deploying and operating AI services in production
• AI observability experience (monitoring, tracing, evaluation, cost optimisation) and familiarity with tools such as Arize Phoenix, Langfuse or Langsmith
• Ability to collaborate across disciplines and influence platform direction

• collaboration across engineering teams
• ability to influence architecture in a small senior team
• adaptability in fast-moving environments
• Python
• TypeScript
• REST APIs

…