Sr. AI Engineer - Contract - Remote - 6 months+

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
• Python and LLM integration, including MCP and A2A orchestration
• Experience with Kubernetes, Cloud Run, Dataflow or Pub/Sub

Responsibilities

• 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
• 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

Full Description

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.