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 production3+ years coding Python in a production cloud environment2+ years deploying ML or agentic systems with CI/CD, on-prem and in the cloud2+ years using orchestration frameworks such as LangGraph, LangChain, OpenAI Agents, or ADKExperience building agents with local and cloud LLMs including API integration, tool calls, workflows, and state managementExperience orchestrating agent inputs and outputs, including pre-processing, post-processing, routing, guardrails, validation, and evaluationExperience with SQL (aggregation, window functions, filter, group data)Experience with Git for version control and collaborationExperience with GPU-mounted containers for development and inference workflowsExperience hardening container images, including distroless patterns and CVE scanningStrong analytic and communication skills across technical and business audiencesBachelor's degree in data science, statistics, CS, engineering, or a related field Preferred Qualifications: Experience deploying local LLMs with vLLM or SGLangExperience with CUDA, TensorRT, and TensorRT-LLM for GPU inference optimizationExperience with LLMOps, including evaluation, tracing, monitoring, and prompt or version managementExperience leading AI projects end to end and mentoring junior colleaguesAdvanced degree in data science, statistics, CS, engineering, or a related field