Resource 1 is seeking a Senior AI Engineer for a long-term, remote contract with our client in the Healthcare industry. Initial contract duration is 6 months, with expected extensions. This can be done 100% remotely from anywhere in the US. Selected individual will be brought in to help develop and deliver next-generation AI solutions across the healthcare enterprise. This role is hands-on and ideal for an engineer experienced in building GenAI and multi-agent systems using modern AI frameworks and Google Cloud Platform (GCP). Will collaborate closely with other engineers to design, build, test, and optimize AI capabilities within a scalable production environment.
Key Responsibilities:
• Develop and enhance enterprise-scale multi-agent systems leveraging LLMs and autonomous agent frameworks, using tools such as Google ADK, Agentspace, MCP, RAG, and A2A orchestration.
• Contribute to the design and implementation of RAG pipelines using BigQuery and Vertex AI for knowledge grounding and factual response accuracy.
• Implement and tune agent reasoning workflows including orchestration, grounding, decision-making, and multi-step reasoning.
• Build and support distributed training workflows, online inference systems, and low-latency serving architectures leveraging Google Cloud services.
• Develop secure and scalable AI components including reusable orchestration layers, connectors, and observability hooks.
• Participate in developing agent governance and compliance frameworks aligned with enterprise standards.
• Translate business features and requirements into technical implementation tasks and contribute to solution design discussions.
• Support deployment pipelines, operational monitoring, troubleshooting, and optimization of production AI systems.
Required Qualifications:
• Degree in Computer Science, AI/ML, or related technical field.
• Hands-on experience in Generative AI and agentic AI development.
• 4–5 years of total experience in AI/ML engineering or applied machine learning.
• Experience building and deploying production AI/ML systems.
• Solid understanding of modern model architectures including transformers, embeddings, and prompt engineering concepts.
• Hands-on expertise with Vertex AI (training, pipelines, deployment, orchestration, and monitoring) and Google Cloud native AI services.
• Experience with one or more agent frameworks (i.e. Google ADK/ Agentspace, LangChain/ LangGraph, LlamaIndex, CrewAI or AutoGen)
• Python and LLM integration, including MCP and A2A orchestration.
• Experience with Kubernetes, Cloud Run, Dataflow or Pub/Sub.
Preferred Qualifications:
• Experience with AI observability, responsible AI frameworks, and model monitoring tools (Vertex AI Monitoring, BigQuery logging, Looker dashboards).
• Experience with multi-modal models and/or advanced optimization strategies.
• Contributions to open-source AI tooling or published applied work.
