Network Engineer Jobs

About The Position

Requirements

• Approximately six years of experience building and running production systems, including at least three years owning cloud infrastructure as code.
• Production cloud engineering experience, preferably with Azure; equivalent AWS or GCP experience is considered. Experience should include Terraform or Bicep and virtual networks, private endpoints, managed identities, role-based access, secrets, and policy.
• Strong grasp of fundamental AI/ML principles, such as train/test/validation, overfitting, calibration, and evaluation methods.
• Hands-on experience provisioning AI workloads, including model-serving endpoints, quota and capacity, GPU compute, and cost controls.
• Experience building and running an LLM-based system in production beyond the demo stage, including tool calling or agents, retrieval, evaluation, and tracing.
• Experience working under HIPAA, HITRUST, SOC 2, FedRAMP, or a similar control framework, and translating controls into configuration and evidence.
• Daily practice using coding agents such as Claude Code, GitHub Copilot, Codex, or Cursor.
• Strong proficiency in Python, containers, and Kubernetes or an equivalent orchestrator.
• Demonstrated ability to change team practices without managing the team by establishing useful, repeatable patterns that reduce team burden and shorten time to solution or insight.
• Ability to prioritize what to build with incomplete information and ship working versions early.
• Bachelor’s degree in Computer Science, Engineering, or a related field preferred; equivalent experience is considered.

Nice To Haves

• Experience with Microsoft Foundry, Foundry Agent Service, Azure OpenAI, or Azure API Management as an AI gateway.
• Experience with Databricks, including Unity Catalog, Model Serving, and MLflow.
• Experience serving open-weight models with vLLM, SGLang, or similar technologies, including quantization and GPU capacity planning.
• Experience building MCP servers or other tool interfaces over existing APIs and legacy systems.
• Experience with agent security, including prompt-injection defenses, tool permissions, and sandboxing.
• Experience operating conventional machine learning, including training pipelines, model registries, and drift monitoring.
• Experience with HL7 FHIR or EHR integration.
• Experience in organ donation and transplant is a plus.

Responsibilities

• Provision Azure AI infrastructure as code, including model deployments in Microsoft Foundry and Databricks, GPU capacity, agent runtimes, networking, identity, and secrets.
• Deploy open-weight and frontier models on UNOS infrastructure using patterns approved by Security and Privacy for protected health information (PHI).
• Develop technical policies and platform controls, including per-agent identities, least-privilege access, private endpoints, allow-listed models, and audit evidence generated through normal use.
• Operate shared model access across providers, including routing, quotas, tracing, and cost attribution by team and use case.
• Build sandboxed environments for engineers to run coding agents against real repositories without production credentials.
• Define and publish standard patterns for agentic development through working templates and reference implementations.
• Integrate AI into CI/CD for pull-request review, test-failure triage, and security findings.
• Build and ship UNOS agents for UNOS One products and internal operations, including tool access, retrieval, orchestration, and human approval where needed.
• Build a path from prototype to production in UNOS One so that proofs of concept can ship without being rebuilt.
• Own evaluation and release for agents and conventional models, including test sets, staged rollout, rollback, and monitoring.
• Baseline and track time from idea to working proof of concept and the quality of shipped work.
• Teach agentic development through pairing, working sessions, and code review, and mentor engineers in the AI function.
• Recommend build-or-buy decisions on AI platforms and tools, stating cost and risk.
• Perform other duties and support additional administrative priorities consistent with the general scope and level of the position.