Software Engineer Manager (AI)

Role: Software Engineer 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!

Role Overview:-

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.

Required Qualifications:

Domain

• 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.

AI & Engineering

• 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.

Cloud & Data

• 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.

Security & Compliance

• 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.

Delivery & Leadership

• 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.

Preferred Qualifications:

• 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.