Required Qualifications & Experien
c
e Core AI/ML & Agentic Engineering (Must-Hav
e)8+ Years in software/AI engineering, with 3+ years directly building, deploying, and maintaining production-grade LLM applications, RAG pipelines, or autonomous agent framework
s.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 microservice

s.
Domain & Architecture Fo
cusHealthcare / Payer Domain: Proven familiarity with Payer workflows (Prior Authorization, Claims Processing, Appeals, Member Engagement) and health data standards (FHIR, EDI X12, ICD-10/CP
T).Data & Retrieval: Experience with vector indexing, hybrid search, reranking strategies, and chunking optimization for massive unstructured document stor
es.Security & HIPAA: Deep understanding of HIPAA compliance, PHI handling, and data privacy in AI pipelin

es.
Nice-to-Have / Force Multipl
iersGCP Cloud Architecture: Experience with Terraform, GCP VPCs, and IAM fundament
als.Fine-Tuning & Small Language Models (SLMs): Experience fine-tuning domain-specific models (PEFT, LoRA) for structured extraction or classificat
ion.Evaluation & Evals Frameworks: Deep experience with automated LLM benching and continuous integration testing for probabilistic softw

are.
Certifications: GCP Professional Machine Learning Engineer or GCP Professional Cloud Architect crede

ntial

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Lead AI/ ML Engineer with GCP and Senior AI/ ML Engineer with GCP

Falcon Smart IT (FalconSmartIT)