Design and implement database-driven operational workflows that automate data transformation, validation, and configuration processes.
Integrate LLM or AI services into structured workflows where appropriate, enabling autonomous processes that can be triggered, executed, logged, and monitored reliably.
Partner with solution architects to convert technical designs into scalable, maintainable implementations.
Establish structured data contracts and schemas to ensure clarity and consistency across systems.
Implement appropriate guardrails, logging, monitoring, and observability practices to support operational stability.
Utilize Microsoft Azure services (Functions, App Services, Logic Apps, Azure AI) to design solutions that are modular, version-controlled, and CI/CD enabled for continuous improvement.
Integrate LLMs into structured database workflows and support retrieval-based (RAG) patterns.

2–5+ years of production experience in SQL, C#, Python, or JavaScript
Strong relational database design, scripting, and query optimization skills.
Experience integrating AI or LLM services, with exposure to frameworks like Semantic Kernel, Copilot Studio, or AI Foundry.
Demonstrated ability to build scalable, repeatable solutions and move from concept to production in ambiguous environments.
Strong problem-solving skills in ambiguous environments with the ability to work seamlessly across product, integration, and delivery teams.
Strong Cross functional work experience with Engineering, Implementations, or Security teams.
Experience building and deploying applications in the Microsoft Azure ecosystem.
Familiarity with CI/CD pipelines and structured Git workflows.
Experience in healthcare SaaS environments
Familiarity with HL7, FHIR, or healthcare data standards
Understanding of retrieval-based workflows or vector databases.
Exposure to Ai Agent Orchestration or Multi-Agent workflows

Solution Engineer – Technical Services

Key skills