• Design and implement multi-agent AI systems using frameworks such as LangChain, AutoGen, and CrewAI. • Build RAG (Retrieval-Augmented Generation) pipelines with vector databases like Pinecone or Weaviate. • Implement agent orchestration patterns and inter-agent communication protocols for distributed AI workflows. • Develop LLM fine-tuning workflows and optimize prompt engineering for production use. • Design and deploy Microsoft Copilot Foundry solutions with custom knowledge bases and integration workflows. • Develop backend services using C# /.NET (ASP.NET Core, Entity Framework, SignalR, Minimal APIs) and Python (FastAPI, Django, Flask). • Implement microservices and containerized deployments using Docker and event-driven architectures with Azure Service Bus or RabbitMQ. • Integrate Azure services including Azure Functions, Azure Logic Apps, Azure Cognitive Services, Azure OpenAI Service, and Azure Data Factory. • Build and maintain CI/CD pipelines and infrastructure as code using Azure DevOps, ARM/Bicep, or Terraform. • Mentor junior developers, document architecture decisions, and collaborate with product managers and data scientists. • Balance technical debt with feature delivery while considering scalability, maintainability, code quality, testing, and documentation. • Implement monitoring and observability using Application Insights. • Apply Git workflow management and branching strategies in collaborative development environments.

• Design, develop, and implement AI-powered features across healthcare product platforms and operational systems. • Build full-stack applications using modern AI engineering workflows and tools such as Cursor, Claude, Codex, OpenAI APIs, and related LLM technologies. • Collaborate with product managers, designers, engineers, and clinical stakeholders to deliver scalable, user-focused solutions that improve patient engagement, care coordination, and operational efficiency. • Develop APIs, backend services, automation pipelines, and AI workflows that support intelligent product capabilities and production-ready deployments. • Apply software engineering, DevOps, and MLOps best practices to testing, deployment, monitoring, and optimization of AI solutions. • Research emerging AI technologies, LLM implementation patterns, and modern product engineering frameworks to continuously improve platform capabilities. • Navigate ambiguity, solve complex technical challenges, and collaborate effectively across technical and non-technical teams in a fast-paced Agile environment. • Take on additional tasks and responsibilities as needed to support team objectives and ensure the success of the project.

• Design, develop, and implement AI-powered features across healthcare product platforms and operational systems. • Build full-stack applications using modern AI engineering workflows and tools such as Cursor, Claude, Codex, OpenAI APIs, and related LLM technologies. • Collaborate with product managers, designers, engineers, and clinical stakeholders to deliver scalable, user-focused solutions that improve patient engagement, care coordination, and operational efficiency. • Develop APIs, backend services, automation pipelines, and AI workflows that support intelligent product capabilities and production-ready deployments. • Apply software engineering, DevOps, and MLOps best practices to testing, deployment, monitoring, and optimization of AI solutions. • Research emerging AI technologies, LLM implementation patterns, and modern product engineering frameworks to continuously improve platform capabilities. • Navigate ambiguity, solve complex technical challenges, and collaborate effectively across technical and non-technical teams in a fast-paced Agile environment. • Take on additional tasks and responsibilities as needed to support team objectives and ensure the success of the project.

• Lead a team of software engineers building scalable services, APIs, and SDKs that power our digital merchandising platform. • Work cross-functionally with other technical leads to establish shared prioritization frameworks and ensure delivery stays aligned with roadmap goals • Drive architecture and design decisions for the ads platform, setting technical direction and building consensus across the team in conjunction with staff engineers • Work with Product Managers to make Jane’s advertising product offerings sound, robust and easy to use. • Work with Data Scientists and Machine Learning Engineers to collect data, analyze data, and use data to improve advertising through iterations. • Own and evolve engineering standards for the team, including code quality, review culture, and technical process • Perform and participate in design reviews and code reviews. • Identify and resolve performance bottlenecks through delegation. • Manage and grow a team of 3-4 engineers through regular 1:1s, goal-setting, and performance feedback • Partner with engineering leadership on hiring: help define roles, evaluate candidates, and assess technical leveling • Identify gaps in team capability or process and propose concrete improvements. You don't wait to be asked.