What are the responsibilities and job description for the AI Engineer @ W2 position at Cyber Sphere LLC?
AI Engineer
Worcester MA
Long Term
W2
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Required qualifications
- 4 years in AI/ML engineering or applied ML in production systems.
- Hands-on with Azure AI: Azure OpenAI / AI Foundry, Azure ML, Azure AI Search, and/or Azure AI Document Intelligence.
- Strong experience building RAG systems (chunking, embeddings, retrieval evaluation, grounding, citation, safe refusal patterns).
- Proficiency in Python for AI/ML services; comfort consuming/producing REST APIs.
- Practical MLOps experience: versioning, automated evaluation, monitoring, and secure cloud deployment.
- Clear understanding of assistive vs authoritative AI in regulated workflows; ability to design human-in-the-loop systems.
- Working knowledge of HIPAA (or equivalent regulated-data) practices: least privilege, secrets management, PHI/PII handling in AI pipelines.
- Ability to turn product requirements into testable AI acceptance criteria and ship iteratively.
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Nice to have
- Experience with Microsoft Power Platform AI patterns (Copilot Studio, adapters/connectors, Dataverse integration).
- Exposure to rules engines / DMN (e.g., Drools or similar) and how ML scores feed decision tables without becoming the decision authority.
- Entity resolution, fuzzy/phonetic matching, or deduplication assist patterns.
- Prior work in Medicaid / MMIS / MES, provider enrollment, credentialing, or other CMS-regulated healthcare systems.
- Experience supporting responsible AI / GenAI disclosure documentation for public-sector or regulated programs (supporting Architecture/Proposal not owning RFP authorship).
- Familiarity with Kubernetes/AKS, API gateways, and Azure network isolation for AI workloads.
- Domain exposure (as examples only not required ownership) such as:
o Screening vendor strategy evaluating aggregator / CVO / sanctions feeds and integration patterns via an enterprise service bus
o DMN / business rules ACA categorical risk tiers, appeal-defensible decision tables, rule versioning
o Network adequacy spatial coverage analytics, geo tooling, or adequacy reporting feeds
o Multi-state productization configuring state-specific adapters while keeping a shared AI platform core
Munesh
,
CYBER SPHERE LLC