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Senior AWS Analytics Engineer. Posting contains no detailed responsibilities or qualifications beyond the job title.

No responsibilities or details were provided. The posting only lists the job title "AI Engineer" with no additional information about duties or expectations.

Design and deploy enterprise-grade generative AI systems across the 7-layer stack, select and fine-tune models, build LLMOps pipelines and observability, integrate with cloud platforms and APIs, enforce data protection, manage hallucinations, lead technical strategy, and act as onshore client technical liaison.

Design, build, and maintain both front-end and back-end components of web applications as a Full Stack Developer. Collaborate with cross-functional teams to implement features, fix bugs, and support deployment and maintenance.

Prepare, review, and send outgoing audit letters; monitor delivery confirmations and reprocess failures; handle chats and email correspondence; escalate issues, report system/workflow problems, and comply with HIPAA and quality/productivity standards to support the audit process.

Handle escalated inbound calls and provider communications, research payer systems for refund/claim questions, log and return voicemails, monitor email/chats, escalate issues, meet quality/productivity standards, and comply with HIPAA.

Design and implement Infrastructure as Code and automation (Terraform, Bicep, ARM, CloudFormation). Build reusable modules, automate provisioning, and develop pipelines (Azure DevOps, GitHub Actions, Jenkins). Script in Python, PowerShell, Bash and use Ansible. Manage hybrid infrastructure across Azure, AWS, VMware and Windows Server, ensuring HA, DR, capacity planning and lifecycle. Enforce security baselines, Zero Trust, identity (Azure AD/Entra/AD), patching, vulnerability management, and compliance (SOC1/2, SOX, HIPAA, PCI, ISO27001).

Lead strategy, planning, execution, and optimization of paid digital media across search, social, display, video, programmatic, and emerging channels. Manage large media budgets, vendor/client relationships, analytics and reporting, and mentor a cross-functional paid media team to meet acquisition, retention, and revenue KPIs.

Senior Business Analyst for insurance data and systems: elicit and document business/functional requirements, create BRDs/FRDs and user stories, perform SQL-based data analysis and source-to-target mappings, support testing (SIT/UAT), collaborate with stakeholders, data engineers, QA and delivery teams across end-to-end Agile project lifecycle.

Lead and own end-to-end delivery of enterprise Data & AI programs, define data strategy and architecture (lakehouse/warehouse), drive modernization, governance, data quality, metadata/lineage, and AI adoption. Manage client relationships, account growth, program budgets, delivery teams, and stakeholder communications to ensure on-time, on-budget outcomes.