Software Engineer Manager (AI)

Role: Software Engineering Manager (AI)



Location: Charlotte, North Carolina (NC)



Work Model: Hybrid, 3 days a week in Charlotte Office (108 Providence Road, Charlotte, NC)



Pay Rate: $100/hr C2C or $180K with health insurance W2



Interview Process : 1 round; In-person in Charlotte

Let's create our future together at The AES Group!

We are seeking an experienced Software Engineering Manager to lead the development and delivery of secure, scalable healthcare technology and AI solutions.
This role is ideal for a hands-on engineering leader who combines strong people management with deep technical expertise across Azure, Python, AI/ML, healthcare data, and regulated environments .







Key Responsibilities

• Lead, mentor, and develop software engineering teams while maintaining strong engineering standards and delivery accountability.

• Provide hands-on technical leadership across application architecture, cloud platforms, AI/ML solutions, APIs, data pipelines, and integrations.

• Design, build, and operate production-grade LLM, RAG, NLP, and agent-based AI applications .

• Drive Azure architecture across compute, data, identity, security, monitoring, and application services.

• Establish and maintain CI/CD, infrastructure-as-code, automated testing, and DevOps practices.

• Ensure healthcare solutions meet HIPAA, HITECH, privacy, security, and compliance requirements , including secure PHI handling.

• Establish controls for encryption, RBAC, secrets management, audit logging, data de-identification, and secure software development.

• Lead Agile delivery using measurable engineering and delivery metrics while remaining accountable for timelines, quality, and outcomes.

• Partner with executives and non-technical stakeholders to communicate architecture, risks, tradeoffs, and delivery decisions clearly.

• Support technical and compliance reviews for healthcare AI solutions, including model evaluation, governance, security, and clinical validation.

• 10+ years of software engineering experience, including 2+ years managing engineering teams.

• Healthcare technology experience, preferably involving Epic, HL7, FHIR, patient access, patient experience, or revenue cycle workflows .

• Experience developing and operating solutions within a HIPAA-regulated environment .

• Production experience delivering AI/ML solutions , including LLM applications, AI agents, RAG pipelines, or NLP systems.

• Demonstrated hands-on technical depth, with the ability to explain code and architecture personally developed within the past two years.

• Strong Python expertise plus experience with at least one of Java, TypeScript, or Go .

• Experience with CI/CD, infrastructure as code, automated testing, Docker, and modern DevOps practices.

• Strong Microsoft Azure experience across compute, data, identity, security, and monitoring.

• Experience with Azure App Service, Azure Functions, AKS, Azure API Management, Azure Storage, Azure SQL/Cosmos DB, Key Vault, and Entra ID .

• Experience with SQL, data pipelines, Databricks or Microsoft Fabric, and healthcare data models.

• Strong understanding of HIPAA/HITECH, PHI protection, privacy, and healthcare security controls.

• Experience with encryption in transit and at rest, least-privilege access, RBAC, audit logging, secrets management, PHI de-identification/redaction, and code/dependency scanning.

• Experience leading Agile delivery with measurable metrics and accountability for schedule and quality.

• Excellent written and verbal communication skills, with the ability to explain complex technical concepts and tradeoffs to executive audiences.

• Experience with Azure OpenAI, Azure AI Foundry, LangGraph, agent orchestration, model evaluation, guardrails, and AI observability .

• Contact center, IVR, conversational AI, or patient messaging experience.

• Experience with AI governance, model risk management, bias testing, and clinical validation.

• Experience supporting security and compliance reviews for healthcare AI.

• Experience managing blended teams consisting of internal engineers, vendors, and offshore resources.

• Experience with Azure AI Search, vector databases, LLM tracing, and evaluation frameworks.