PROJECT DESCRIPTION

We are looking for a Platform Engineer with strong experience in cloud infrastructure and a passion for AI-powered automation. This is not a traditional DevOps or admin role — we’re seeking someone who builds usable tools and automations, not just infrastructure, and uses AI actively to accelerate their own work.
You will play a key role in our corporate-wide initiative to redefine access to AI by developing and operating a platform that empowers teams to experiment with and deploy foundational and AI models, intelligent agents, and automated workflows at scale.
You should already be using AI tools (e.g. ChatGPT, Copilot, Claude, agent builders, etc.) in your daily work and clearly understand how they improve your efficiency.
Our client is a global organization on a mission to make AI accessible across the enterprise. The platform provides a foundation for safe, scalable, and rapid AI adoption — from intelligent agents to internal copilots. This role directly shapes how thousands of users across the company leverage AI for impact.

SKILLS

Must have
Proven software development experience (e.g., Python, TypeScript, or similar)
Hands-on experience automating real-world processes or building internal tools
Solid cloud infrastructure experience with AWS (EC2, IAM, S3, Lambda, CloudWatch, etc.)
Experience with Terraform or CDK for provisioning infrastructure
Familiarity with CI/CD pipelines and Git-based workflows
Active use of AI tools for development, documentation, research, or automation
Strong problem-solving mindset and ability to work autonomously across teams
Nice to have
Experience with Kubernetes (especially EKS) and Helm
Exposure to foundational model hosting (e.g. HuggingFace, vLLM, Triton)
Understanding of RAG pipelines, embeddings, and vector databases (e.g. Weaviate, Qdrant)
Familiarity with AI automation libraries like LangChain, Haystack, or similar
Observability stack: Prometheus, Grafana, OpenTelemetry

Build internal tools, automation scripts, and developer-facing interfaces to enable AI-powered workflows
Develop and maintain cloud-based infrastructure (AWS) to support hosting of foundational models and intelligent agents
Implement Infrastructure-as-Code practices using Terraform/CDK
Work closely with internal teams to embed AI capabilities into business processes via APIs, agents, or prompt workflows
Contribute to reproducible, scalable, and observable environments for AI and automation use cases
Promote and apply responsible automation practices across the engineering organization