AI Engineer @ W2

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

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CYBER SPHERE LLC