Sr AI & Software Engineer

Rōnin Consulting is hiring a senior engineer for a contract-to-hire engagement supporting a Fortune 500 healthcare client. The role leads production Generative AI development and integrates AI systems into secure, enterprise-grade full-stack applications, while providing technical leadership and collaborating with business and clinical stakeholders.

Responsibilities:

• Lead the design, development, and deployment of scalable, production-grade Generative AI solutions on enterprise cloud platforms (GCP Vertex AI / Gemini, AWS Bedrock / SageMaker, or Azure AI Foundry / Azure OpenAI)
• Architect and build sophisticated Retrieval-Augmented Generation (RAG) systems that ground LLMs in proprietary and domain-specific data, ensuring response accuracy and factual reliability in regulated healthcare contexts
• Design and implement efficient data pipelines for preparing, processing, and embedding data into vector stores, with attention to data governance and compliance requirements
• Develop grounding strategies and design the data structures needed to connect LLMs with enterprise and real-time information sources
• Design and implement agentic AI systems capable of complex reasoning, multi-step task execution, and autonomous operation using frameworks such as LangChain, LangGraph, Google ADK, or custom orchestration
• Integrate the Model Context Protocol (MCP) to standardize LLM-to-tool communication and enhance system interoperability where applicable
• Build and deploy evaluation frameworks, guardrails, and monitoring to ensure model reliability and safety in production
• Perform proof-of-concept and proof-of-technology work to secure stakeholder buy-in for new AI initiatives
• Design client-side and server-side architecture with clearly defined AI integration points and attention to security and data protection in healthcare environments
• Build enterprise-grade applications in your language of strength (Python, Java, Node.js, C#, or similar), including APIs, services, and integrations with AI endpoints and third-party platforms
• Develop and manage robust SQL and NoSQL databases and application layers, including reusable data objects and automated testing frameworks
• Work with Docker/Kubernetes, serverless, and microservice architectures in cloud-native environments
• Implement security, data protection, and compliance controls appropriate to healthcare and enterprise environments
• Partner with data scientists and AI engineers to optimize intelligent features, pipeline performance, and system reliability
• Explain complex AI architectures and trade-offs clearly to non-technical and mixed business/technical stakeholders in a healthcare enterprise context
• Provide technical mentorship and foster a collaborative, growth-oriented team environment
• Lead investigations and solution proposals for complex engineering and design challenges in the AI domain
• Guide team members in scope-of-work estimation and forecasting for AI-related projects
• Collaborate with business stakeholders, product owners, and clinical or operational teams to capture functional and non-functional requirements
• Drive delivery using Agile practices and principles; write clear technical documentation for systems, APIs, and AI workflows