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Lead the design, administration, automation, and operational support of highly available Kafka platforms across GCP and on-premises Kubernetes environments. Responsibilities include capacity planning, disaster recovery, Kafka Connect integrations, infrastructure automation, monitoring, incident response, upgrades, security, documentation, and 24x7 on-call support. The role also drives platform architecture, reliability improvements, stakeholder recommendations, and AI-enabled operational efficiencies.

Owns end-to-end design, development, testing, deployment, DevOps, and production support for secure, scalable applications using Angular, .NET Core, Azure, SQL Server, and Kubernetes. Drives application modernization, cloud-native architecture, automation, CI/CD, testing strategies, production troubleshooting, and technical debt reduction. Collaborates with product, business, architecture, QA, and DevOps teams while mentoring engineers and applying AI-assisted development practices.

Leads the design, development, and support of enterprise Amazon Connect contact center solutions. Provides technical leadership, architecture guidance, code and design reviews, mentoring, integrations, cloud-native AWS development, conversational AI implementation, digital engagement support, production deployments, monitoring, and incident resolution. Builds contact flows, routing logic, serverless applications, APIs, and integrations across customer and agent channels.

Leads hands-on software engineering enablement by developing code samples, labs, demos, and reference implementations. Delivers technical training, live coding, workshops, and debugging support while embedding cloud-native, secure, compliant, AI-assisted development practices. Partners with instructional designers, cloud and security experts, and platform owners to maintain accurate learning pathways and continuously improve technical content.

Develop and maintain scalable Java web applications, RESTful APIs, backend services, and responsive frontend applications. Optimize databases and SQL queries, implement cloud-native solutions across AWS, Azure, and GCP, and use DevOps, CI/CD, Docker, and Kubernetes for automated deployments. Collaborate with distributed teams, apply secure coding and modern software engineering practices, and support AI/ML initiatives in healthcare.

Provides technical leadership for enterprise software engineering teams. Designs and implements scalable Azure, .NET, and Angular cloud applications, while leading AI, ML, Generative AI, RAG, LangChain, and LangGraph initiatives. Mentors engineers, establishes engineering standards, guides architecture and technology decisions, and drives DevOps, CI/CD, security, testing, observability, and operational excellence. Collaborates with product, data, architecture, and business teams to deliver reliable, secure, and innovative solutions.

Leads design, development, support, modernization, and production issue resolution for RxClaim pharmacy claims adjudication systems. Provides technical leadership across Synon, AS400/iSeries, DB2, COBOL, and related platforms; partners with cross-functional teams; mentors engineers; and drives Agile delivery, governance, reliability, regulatory compliance, and AI-enabled engineering improvements.

Design, develop, deploy, and maintain scalable AI/ML solutions across the full model lifecycle. Build ML pipelines, integrate models into enterprise applications, implement MLOps practices, monitor production performance, and develop solutions using NLP, deep learning, predictive modeling, and Generative AI. Collaborate with product, engineering, and business teams, mentor junior engineers, promote Responsible AI, and contribute to reusable frameworks and engineering standards.

Leads strategy, roadmap, and end-to-end delivery of enterprise Agentic AI solutions. Owns product prioritization, PI planning, release execution, dependency management, governance, stakeholder alignment, and adoption. Partners with engineering, data science, architecture, platform, security, compliance, and business teams to translate objectives into AI capabilities, technical requirements, workflows, and automation. Evaluates AI platforms and LLMs while supporting responsible AI, privacy, security, and organizational change initiatives.

Leads enterprise software engineering and AI-driven development transformation. Designs and optimizes Java applications using Spring Boot, microservices, REST APIs, cloud-native architecture, and modern data platforms. Establishes AI-assisted engineering standards, governance, testing, agentic workflows, and productivity metrics. Drives modernization, technology roadmaps, proof-of-concepts, organizational change, training, and adoption of AI-native delivery practices while mentoring engineers and partnering with architecture, product, QA, DevOps, and business teams.