Architect multi-agent systems for AIOps, including anomaly detection, event correlation, ITSM ticket triage, and self-healing runbooks that reduce mean time to detect (MTTD) and mean time to resolve (MTTR)
Lead the design of agents that generate, review, and validate Infrastructure as Code (Terraform, Bicep), with policy checks and automated validation built into CI/CD pipelines before changes reach production
Develop FinOps agents that identify cost anomalies, rightsizing opportunities, and idle resources, and act on them within defined guardrails
Design security and compliance agents for posture assessment, configuration drift detection, and automated collection of audit evidence
Establish AI governance for agent operations, including human-in-the-loop approvals, access controls, guardrails, audit logging, and responsible AI practices suited to a regulated healthcare environment
Partner with business stakeholders, clients, and engineering teams to define and architect end-to-end Cloud and AI solutions aligned with strategic objectives
Lead architecture for data and analytics platforms, including Azure Databricks and the data foundations that support AI workloads
Drive operational excellence, including monitoring, logging, observability, resiliency, and disaster recovery, for both Cloud platforms and the agents that run on them
Establish and promote architecture standards, reusable agent patterns, and reference architectures across the organization
Translate complex technical concepts into clear business value for clients and executive stakeholders, including measurable outcomes from AI adoption
Evaluate emerging AI technologies, frameworks, and models, and keep improving the organization’s Cloud and AI capabilities and innovation roadmap
Required Qualifications
15+ years of experience in IT, with at least 10 years focused on Cloud architecture (Azure preferred)
3+ years of hands-on experience with AI/ML, including at least 2 years building and deploying LLM-based or agentic AI solutions in production
Experience leading and developing engineering teams, including hiring, coaching, and setting technical direction
Hands-on experience with Azure AI Foundry, Azure OpenAI, and agent frameworks
Working knowledge of agent design patterns, including tool use, multi-agent orchestration, retrieval-augmented generation (RAG), and Model Context Protocol (MCP)
Experience applying AI or automation to Cloud operations (AIOps, automated remediation, IaC generation, FinOps, or security posture management)
Proven track record of working directly with clients and cross-functional development teams to deliver enterprise solutions
Deep expertise in Microsoft Azure services, including compute, storage, security, and platform services
Hands-on experience with Azure Databricks and modern data architecture (data lakes, ETL/ELT, streaming, lakehouse)
Strong communication and presentation skills, with the ability to influence both technical and executive stakeholders
Preferred Qualifications
Experience with AWS or Google Cloud in addition to Azure
Experience in healthcare or other regulated industries, including HIPAA and handling protected health information (PHI)
Familiarity with AI governance frameworks such as the NIST AI Risk Management Framework
Experience with LLMOps practices, including agent evaluation, prompt and model versioning, and monitoring agent behavior in production
Relevant certifications such as Azure Solutions Architect Expert or Azure AI Engineer Associate
Core Competencies
Excellent communication skills with the ability to explain complex technical and AI concepts to both technical and non-technical audiences
Ability to provide clear and concise status reports against roadmap and overall adoption strategy
Strong leadership skills, with the ability to build a team, set clear direction, and develop people
Strong collaboration skills and ability to work effectively with clients, stakeholders, and cross-functional teams
Client-focused mindset with the ability to build trusted relationships and deliver solutions aligned to business goals
Strong analytical and problem-solving skills with the ability to make sound decisions in complex environments
Pragmatic approach to AI adoption, balancing innovation with security, reliability, and risk
Highly organized and results-driven, with the ability to manage multiple priorities and meet deadlines
Commitment to quality, operational excellence, and continuous improvement
Travel
Up to 20% travel may be required for client meetings, project work, or team collaboration
Our company complies with all local/state regulations in regard to displaying salary ranges. If required, the salary range(s) are displayed below and are specifically for those potential hires who will perform work in or reside in the location(s) listed, if selected for the role. Any offered salary is determined based on internal equity, internal salary ranges, market data, ranges, applicant's skills and prior relevant experience, certain degrees and certifications (e.g. JD, technology), for example.
Salary range: $140,000 - $170,000 USD. The salary range reflects the anticipated base salary for this position at the time of posting. Final compensation may vary based on factors including experience, skills, education
