• Design and deploy production-grade AI and machine learning models. • Build, test, and deploy predictive and generative AI models into cloud-based environments optimized for Medicare Advantage workloads. • Maintain rigorous monitoring and drift detection to preserve model integrity over time. • Build and operate intelligent process automation solutions. • Identify and automate high-volume, repetitive business processes using RPA platforms and orchestration tools. • Develop and maintain AI/ML data infrastructure and pipelines. • Integrate AI models and automation services into enterprise products via REST APIs and microservices. • Monitor, optimize, and ensure system reliability. • Collaborate cross-functionally and advance a culture of AI innovation.

• Architect and deliver production-grade AI and machine learning systems. • Lead the end-to-end design and deployment of predictive and generative AI models — including NLP, classification, regression, and computer vision — for high-stakes Medicare Advantage workloads. • Own architectural decisions related to model selection, scalability, and production readiness, and establish monitoring and drift detection standards adopted across the team. • Lead the design and scaling of intelligent process automation. • Evaluate and architect enterprise-wide automation strategies using RPA platforms (e.g., UiPath, Power Automate) and orchestration tools (e.g., Airflow, Prefect). • Drive automation ROI analysis, establish engineering standards for fault-tolerant workflow design, and serve as the senior technical owner for the organization's most complex automation pipelines. • Own AI/ML data infrastructure strategy and pipeline reliability. • Design and govern robust ETL and feature engineering pipelines that support model training, validation, and real-time inference at scale. • Define infrastructure standards for experimentation, retraining, and monitoring that ensure consistent model performance across a regulated, high-availability production environment. • Integrate AI and automation systems into enterprise architecture. • Lead the integration of deployed models and automation services into enterprise products via REST APIs and microservices, setting the engineering bar for security, HIPAA compliance, and maintainability. • Drive adoption of containerization (Docker, Kubernetes) and CI/CD best practices across the AI engineering team. • Architect and implement LLM-powered and agentic AI applications. • Define the technical approach for integrating large language models into clinical and operational workflows — including prompt engineering, fine-tuning, RAG pipelines, and multi-agent orchestration frameworks (LangChain, LangGraph, AutoGen). • Own delivery of agentic AI solutions that transform end-to-end workflows in areas such as clinical document intelligence, intelligent prior authorization, and member communication. • Establish reliability standards and drive continuous system improvement. • Own the performance, reliability, and scalability posture of AI and automation systems across the team. • Define alerting, testing, and tuning frameworks that proactively surface degradation before it affects member outcomes, and lead post-incident reviews to build organizational resilience. • Mentor engineers and shape AI engineering culture. • Provide senior technical mentorship to mid-level and junior engineers through hands-on code reviews, design critiques, and paired problem-solving. • Contribute to hiring, technical interviews, and the establishment of team-wide engineering standards — including responsible AI practices such as bias detection, model explainability, and governance in high-stakes healthcare contexts.

Role Description We are seeking a new talent to join the Software Engineering team. In this role, you will collaborate on the development of a Cyber Resilience POD for a company that provides healthcare management solutions and services aimed at improving patient care and operational efficiency. - Collaborate with the Automation Lead to design and develop automation components for deployment within the Resilience Pod. - Support deployments across cloud and on-premise environments, including application installation, configuration, and data restoration. - Design, develop, and test automation solutions. - Deliver production-ready solutions along with documentation to support transition to operations teams. - Experience and/or knowledge in Python, Ansible, automation, and Terraform. - Familiarity with infrastructure as code and automation practices (nice to have). Company Description Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. - We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. - Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. - We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. - Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. - We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

• Drive security automation strategy for complex engagements, embedding an audit-by-construction methodology into CI/CD pipelines to ensure continuous compliance. • Architect scalable security solutions for cloud-native and hybrid environments, specializing in the design and governance of secure Azure Landing Zones. • Lead the design of enterprise-grade security platforms, engineering robust tenant isolation strategies to mitigate cross-tenant risks in multi-tenant architectures. • Contribute to compliance strategy and data privacy by implementing automated PII protection mechanisms (e.g., masking, tokenization) and preparing environments for frictionless audits. • Govern identity and access management by developing comprehensive Role-Based Access Control (RBAC) models that enforce the principle of least privilege across all systems. • Mentor senior and mid-level security engineers, developing talent. • Manage stakeholder relationships, providing security risk insights to leadership. • Champion security automation best practices and continuous improvement. • Evaluate emerging security technologies and threat landscapes. • Lead red team/blue team exercises and security assessment programs. • Contribute to compliance strategy and audit preparation. • Design security metrics and reporting frameworks.