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Sr AI & Software Engineer

Job in Nashville, Davidson County, Tennessee, 37247, USA
Listing for: Rōnin Consulting, LLC
Contract position
Listed on 2026-06-04
Job specializations:
  • Software Development
    AI Engineer, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 110000 - 140000 USD Yearly USD 110000.00 140000.00 YEAR
Job Description & How to Apply Below

Sr AI & Software Engineer

Nashville, TN (On-site / Local Candidates Only) Contract-to-Hire | 9-Month Engagement AI Transformation, Integration & Hybrid Cloud

About the Role

Join an elite innovation team at Rōnin Consulting where AI engineering and full-stack software development converge. This is a contract-to-hire engagement — a 9-month contract with a clear path to permanent placement for the right candidate.

As a Sr AI & Software Engineer based in Nashville, TN, you will provide technical leadership designing and delivering production-grade Generative AI solutions for a Fortune 500 healthcare client with a nationwide footprint.

This role demands real production delivery — not POCs, not demos. You will architect Retrieval-Augmented Generation (RAG) systems, agentic workflows, grounding pipelines, and vector store infrastructure, and integrate them into enterprise-grade full-stack applications. The client’s AI stack is centered on enterprise cloud AI platforms — GCP Vertex AI and Gemini are the primary environment, but engineers with equivalent depth on AWS (Bedrock, Sage Maker) or Azure (AI Foundry, Azure OpenAI) are strongly encouraged to apply.

Cloud platform depth matters more than which hyperscaler is on your resume.

This is a role for a senior engineer with 8+ years of experience who thrives at the frontier of AI innovation: equally comfortable designing a vector store schema, building a grounding pipeline, writing a clean API, and translating complex AI concepts for non-technical healthcare stakeholders. Prior healthcare or regulated-domain experience is a meaningful advantage with this client.

Responsibilities

Generative AI & Agentic Systems

  • Lead the design, development, and deployment of scalable, production‑grade Generative AI solutions on enterprise cloud platforms (GCP Vertex AI / Gemini, AWS Bedrock / Sage Maker, 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 Lang Chain, Lang Graph, 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

Full‑Stack Software Engineering

  • 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 No

    SQL 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

Leadership & Collaboration

  • 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…
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