Agentic AI Engineer

About the Opportunity

We’re seeking an Agentic AI Engineer to help design, build, and deploy next-generation AI agents and workflow-driven solutions that support critical healthcare initiatives/decision-making. This role focuses on developing agent-based systems using both local and cloud-hosted LLMs, orchestrating complex workflows, tool integrations, validation layers, and MCP-based architectures within a GCP environment. The ideal candidate brings a strong Data Science, AI/ML Engineering, or Applied Research background, along with hands-on experience developing and deploying cloud-based AI solutions. Advanced degrees (MS or PhD) are strongly preferred, though exceptional candidates with the right technical experience will be considered. You’ll work alongside a highly technical team building production-grade Agentic AI platforms, collaborating closely with engineers and business stakeholders to transform cutting-edge AI concepts into scalable, real-world solutions. Experience with GCP is preferred, though candidates who gained GCP expertise through academic research and have professional AWS or Azure experience are encouraged to apply. This is a fully remote opportunity supporting EST/CST working hours, with a long-term contract-to-hire path for candidates who can work on a W2 basis without current or future sponsorship requirements.

Title Agentic AI Engineer Duration 12mo contract, client goal is conversion to FTE Setting REMOTE (EST/CST schedule) Interview Process 2-3 Rounds Onboarding Process Background Check, Drug Test, Paperwork, ID Verification, References Engagement Type / Work Auth W2, must be able to work on W2 without sponsorship now or any points in the future Compensation $60-70/hr approx.

Position Summary:

We are seeking a motivated Agentic AI Engineer for our Medicare Member Experience team. You’ll design and deploy MCP and agent-based solutions on GCP to improve our Medicare Stars program. You’ll build agents using local and cloud LLMs. You’ll orchestrate agent inputs and outputs, including pre-processing, post-processing, validation, and tool use. You’ll partner with engineers, domain experts, and stakeholders to define objectives and deliver production systems.

Required Qualifications:

• 3+ years using GCP services (BigQuery, Dataproc, Kubernetes, Vertex AI, GKE) - preferably from a production setting, but open to seeing profiles where it was used during school/degrees and had AWS/Azure in enterprise production
• 3+ years coding Python in a production cloud environment
• 2+ years deploying ML or agentic systems with CI/CD, on-prem and in the cloud
• 2+ years using orchestration frameworks such as LangGraph, LangChain, OpenAI Agents, or ADK
• Experience building agents with local and cloud LLMs including API integration, tool calls, workflows, and state management
• Experience orchestrating agent inputs and outputs, including pre-processing, post-processing, routing, guardrails, validation, and evaluation
• Experience with SQL (aggregation, window functions, filter, group data)
• Experience with Git for version control and collaboration
• Experience with GPU-mounted containers for development and inference workflows
• Experience hardening container images, including distroless patterns and CVE scanning
• Strong analytic and communication skills across technical and business audiences
• Bachelor’s degree in data science, statistics, CS, engineering, or a related field

Preferred Qualifications:

• Experience deploying local LLMs with vLLM or SGLang
• Experience with CUDA, TensorRT, and TensorRT-LLM for GPU inference optimization
• Experience with LLMOps, including evaluation, tracing, monitoring, and prompt or version management
• Experience leading AI projects end to end and mentoring junior colleagues
• Advanced degree in data science, statistics, CS, engineering, or a related field