AI Engineer

Role summary

Build and run the AI platform: the backend that gives products governed access to AI models and tools, the infrastructure it runs on, and the AI features built on top of it.

Responsibilities

Build and maintain backend services and APIs (REST, streaming) in Python or Go

Deploy and operate services and AI model servers on Kubernetes, with Helm and CI/CD pipelines

Implement authentication, access control and security controls: OAuth 2.0 / OIDC, API keys, secrets management, sensitive-data masking, audit logging

Select, deploy and operate AI models, commercial and open-weight: LLMs, embedding models and speech models

Build retrieval-augmented generation and agent features: vector and hybrid search, tool calling, multi-step workflows, guardrails

Help teams integrate with the platform's APIs, and build tool services such as MCP servers

Set up monitoring, dashboards and alerts; investigate and resolve incidents

Write technical documentation, code samples and runbooks

Technical requirements

Degree in computer science, engineering or a related field, or equivalent experience

Python; Go is a plus

REST APIs, HTTP and JSON

Linux, Git and Docker

Hands-on experience with at least one LLM API (OpenAI, Anthropic, Google)

Nice to have:

More experience is a plus: professional years in backend, platform or ML engineering, and AI features shipped to production

Kubernetes, Helm, Argo CD and CI/CD (GitHub Actions or GitLab CI)

Model serving with vLLM or Ollama

PostgreSQL, including pgvector, and Redis

OAuth 2.0 / OIDC and a secrets manager such as HashiCorp Vault

LLM or API gateways (LiteLLM, Envoy, Kong) and agent frameworks (MCP, A2A, LangGraph)

Monitoring with Prometheus, Grafana, OpenTelemetry or Langfuse

Experience mentoring other engineers

Work with regulated or sensitive data

Desired Candidate Profile

Technical requirements

Degree in computer science, engineering or a related field, or equivalent experience

Python; Go is a plus

REST APIs, HTTP and JSON

Linux, Git and Docker

Hands-on experience with at least one LLM API (OpenAI, Anthropic, Google)

Nice to have:

More experience is a plus: professional years in backend, platform or ML engineering, and AI features shipped to production

Kubernetes, Helm, Argo CD and CI/CD (GitHub Actions or GitLab CI)

Model serving with vLLM or Ollama

PostgreSQL, including pgvector, and Redis

OAuth 2.0 / OIDC and a secrets manager such as HashiCorp Vault

LLM or API gateways (LiteLLM, Envoy, Kong) and agent frameworks (MCP, A2A, LangGraph)

Monitoring with Prometheus, Grafana, OpenTelemetry or Langfuse

Experience mentoring other engineers

Work with regulated or sensitive data