Our client is currently seeking a Lead Solution & Deployment Engineer
This job will have the following responsibilities :
- Design and implement reusable deployment blueprints for LLMs across Bedrock and Vertex AI, with support for both batch and real-time inference.
- Build infrastructure to manage prompts, chains, retrieval strategies (RAG), and memory in a modular, auditable way.
- Enable secure use of foundation models, including usage quotas, red-teaming sandboxes, API gateways, and runtime policy enforcement.
- Partner with architecture and cyber teams to embed controls aligned with internal AI governance and regulatory expectations.
- Implement observability layers that track model behavior, prompt performance, drift, cost, and data leakage risks.
- Guide application teams in integrating LLMs into downstream products via APIs, workflows, and agents.
Qualifications & Requirements :
6+ years in engineering roles, including experience with LLM application delivery in a cloud environment.Hands-on experience deploying models on AWS Bedrock, Vertex AI, or similar managed foundation model platforms.Proficiency with Python and frameworks such as LangChain, LlamaIndex, or orchestration libraries like Ray, Argo, or Prefect.Deep understanding of prompt tuning, embedding models, retrieval workflows, and agentic decision trees.Experience implementing security, telemetry, or access control for ML or GenAI applications in enterprise environments.