AI/ML GCP Engineer
Remote
Rate: $52-53/hr
Â
Job Description :
Job Requirements Core Stack: GCP (Vertex AI, Cloud Run, GKE), Python, Agentic Frameworks (LangChain/LangGraph, LlamaIndex, AutoGen), Vector DBs, Payer Systems (EDI/FHIR, Claims, Prior Auth).Lead AI/ML Engineer (Forward Deployed) to lead the design, hands-on development, and operationalization of our next-generation Agentic AI Solution Platform built specifically for the Healthcare Payer sector.Key Responsibilities1. Healthcare Payer Agentic Platform ArchitectureDesign and implement end-to-end multi-agent orchestration systems (using LangGraph, AutoGen, CrewAI, or custom DAG runners) 2. Forward Deployed Engineering & Client Value DeliveryEmbed directly with engineering, product, and client business stakeholders to translate messy healthcare operational processes (e.g., prior auth rules, claims denial handling) into deterministic agent tools and graphs.3. Production AI/ML Engineering on GCPBuild, deploy, and maintain high-throughput, low-latency microservices using Python, Docker, Cloud Run, and GKE.4. Healthcare Data, Compliance & SecurityEngineer AI agent tools that interface seamlessly with enterprise Payer data standards, including HIPAA-compliant environments, FHIR/HL7 APIs, and EDI transactions (837, 835, 270/271, 278).5. Observability, Guardrails & Responsible AIDeploy comprehensive telemetry to track agent trajectory, tool calling success rate, token usage, and sub-second reasoning latency using Google Cloud Operations, Required Qualifications & ExperienceCore AI/ML & Agentic Engineering (Must-Have)8+ Years in software/AI engineering, with 3+ years directly building, deploying, and maintaining production-grade LLM applications, RAG pipelines, or autonomous agent frameworks.Agentic Frameworks: Hands-on mastery of multi-agent orchestration patterns, tool calling, stateful graphs, and memory management (e.g., LangGraph, AutoGen, LlamaIndex, Semantic Kernel).GCP AI Ecosystem: Deep experience with Vertex AI (Model Garden, Endpoint Deployment, Vector Search, Workbench) and cloud-native services (Cloud Run, Pub/Sub, Cloud Functions).Production Python Engineering: Advanced Python expertise (AsyncIO, FastAPI, Pydantic, gRPC) writing clean, tested, and containerized microservices.Healthcare / Payer Domain: Proven familiarity with Payer workflows (Prior Authorization, Claims Processing, Appeals, Member Engagement) and health data standards (FHIR, EDI X12, ICD-10/CPT
Â
|
Neha Chaudhary
Survey Link:Â The survey is anonymous, and the information collected will be analysed in aggregate to support initiatives that improve the total experience across Compunnel.
|
Â
—
