AI Engineer – Cloud & Generative AI Solutions

About the role

Join a large global investment bank to lead the design, architecture, and implementation of highly scalable AI‑powered applications. You will work in an agile, cloud‑native environment, delivering compliance archive solutions and advanced generative AI systems on Google Cloud Platform.

Key responsibilities

• Design and deploy end‑to‑end AI solutions, including LLM integration, agentic AI workflows, and RAG architectures using VertexAI, Gemini Model, LangGraph and ADK.
• Lead cloud migration and infrastructure automation on GCP using Terraform, GCE, GKE, CloudRun, CloudSQL/Postgres and BigQuery.
• Establish CI/CD pipelines, container orchestration, observability and automated testing for AI services.
• Mentor engineers, drive technical standards, and collaborate with product, data science and control teams.

Required profile

• 13+ years of experience as an AI Engineer with a proven track record of delivering enterprise‑scale AI solutions.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience.
• Strong understanding of financial markets and investment banking products is highly desirable.

Required skills

• Python, Java (preferred), Scala (plus)
• FastAPI, Spring Boot, RESTful API design
• Google Cloud Platform services: GCE, GKE, CloudRun, Cloud Composer, BigQuery, CloudSQL/Postgres
• Terraform, Git, GitHub/Azure DevOps, CI/CD, Docker, Kubernetes
• Large Language Model (LLM) development, LangGraph, ADK, Vector databases, RAG, LLMOps
• Machine learning libraries, feature engineering, model evaluation, explainability
• Oracle Exadata, relational databases, high‑volume ETL processing
• Observability tools: OpenTelemetry, logging, monitoring
• Agile/Scrum methodologies, JIRA, test‑driven development, automated testing tools