Quick Overview
Job Description
Primary Responsibilities:
• Drive responsible use of AI/ML adoption across the team, driving innovative use of both Generative AI and traditional ML techniques
• Design, develop, test, deploy, maintain, and continuously improve AI-powered software solutions to meet customer and business needs
• Build responsible AI solutions and service components to support the Provider community, ensuring compliance with ethical and regulatory standards
• Develop new features leveraging AI/ML, including Generative AI models, predictive analytics, and automation capabilities
• Provide technical leadership for AI initiatives, including Chatbots and conversational AI solutions
• Partner with product management, architects, and engineering leadership to deliver creative, scalable AI solutions for healthcare challenges
• Drive alignment with enterprise AI strategies and ensure solutions meet business objectives and engineering best practices
• Accountable for high-quality software deliverables and operational excellence
• Mentor and train team members on AI/ML technologies, frameworks, and responsible AI practices
• Collaborate with broader engineering teams to integrate AI into cloud modernization efforts and digital-first initiatives
• Exercise independent judgment to prioritize, plan, and manage AI-related activities and projects
Required Qualifications:
• BS in Computer Science, Engineering, or related technical field (or equivalent experience)
• 6+ years of software engineering experience
• 4+ years of hands-on experience building AI/ML solutions, including LLMs, Generative AI, and traditional ML models
• 4+ years of experience with Web and API development
• 4+ years of experience hosting applications in cloud environments (AWS preferred)
• Solid experience with Chatbots, Conversational AI, and NLP-based solutions
• Solid experience with Agentic AI (MCP or similar agent orchestration frameworks) and Strands Agents
• Solid experience in Python or Java
• Solid knowledge of security, access controls, logging, monitoring, performance tuning, disaster recovery, and production operations
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