Agentic AI Developer

How You'll Make an Impact

As an Agentic AI Developer at Strata, you will be at the forefront of building our next generation of intelligent agents. You will operate under the AI Platform team, working closely with architects, data scientists, platform engineers, and product leaders. You'll design and implement advanced agentic AI solutions that enhance our platform's ability to deliver insights, automation, and decision support. Your contributions will directly impact how healthcare providers leverage financial, operational, and clinical data, helping them deliver exceptional patient care while strengthening their financial performance. By exploring new agentic patterns and incorporating the latest technologies, you'll ensure Strata continues to lead in an evolving AI landscape.

A Day in the Life

• Design, develop, and deploy production grade AI agents that solve real business problems across Strata's products and internal platforms.
• Collaborate with cross-functional teams to translate healthcare and business requirements into agentic workflows and AI-powered applications.
• Build robust multi-agent systems using best practices for agent orchestration, planning, memory management, Retrieval Augmented Generation (RAG), Model Context Protocol (MCP), function calling, and tool integration.
• Evaluate and prototype emerging AI frameworks, foundation models, and developer tooling, identifying opportunities to improve product capabilities, engineering productivity, and platform performance.
• Develop reusable AI services, SDKs, prompt libraries, skills, evaluation frameworks, and agent components that enable scalable adoption across Strata teams.
• Implement automated Eval pipelines, observability, guardrails, cost monitoring, and performance analytics to ensure production quality, reliability, security, and responsible AI practices.
• Partner with AI Platform engineers to optimize model deployment, performance, and infrastructure for enterprise scale.
• Contribute to AI architecture, coding standards, governance, and engineering best practices while mentoring teammates on modern agentic development patterns.
• Communicate technical designs, tradeoffs, and implementation strategies effectively with engineering, product, and healthcare stakeholders.

Our Technology Stack

• Python
• SQL
• AWS
• LLM APIs
• RAG
• Tool calling

Required

• 4-6 years of experience in software development, computer science, or data science/engineering roles
• Experience developing applications using Python and SQL
• Hands-on experience with AWS AI and cloud services, including Amazon Bedrock, AgentCore, SageMaker, S3, Lambda, and related AWS services
• Experience working with modern foundation models through APIs or managed platforms
• Strong understanding of LLM/GenAI model application development, including prompt/loop engineering, system instructions, tool calling, RAG, memory/context management, and MCP
• Experience designing and implementing AI workflows, agent orchestration, and integrating AI capabilities into production applications
• Knowledge of software engineering best practices, including API development, testing, version control, CI/CD, and cloud native application development
• Strong analytical, problem-solving, and debugging skills with the ability to quickly evaluate and adopt emerging AI technologies
• Excellent communication skills with the ability to explain complex technical concepts to engineering, product, and healthcare stakeholders

Preferred

• Experience building and deploying agentic AI systems in production environments
• Experience with agent frameworks such as LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar orchestration frameworks
• Experience designing evaluation frameworks for LLM and agent applications, including automated testing, regression evaluation, hallucination detection, and quality measurement
• Experience implementing AI safety mechanisms, including guardrails, content filtering, prompt injection mitigation, and responsible AI practices
• Experience with observability and monitoring for AI systems, including tracing, token usage, latency, cost monitoring, and production diagnostics
• Experience working with healthcare, financial, or other regulated industry data is a plus