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Designs and delivers enterprise AI architectures spanning generative AI, classical machine learning, LLMs, agentic systems, data pipelines, RAG, model platforms, security, governance, observability, and FinOps. Leads technology selection, architecture decisions, prototypes, reference architectures, and technical workshops. Owns architecture artifacts, mentors cross-functional engineering teams, and ensures scalable, secure, production-ready AI systems aligned with client business objectives.

Lead the design, deployment, automation, and maintenance of secure, scalable Azure cloud infrastructure. Build CI/CD pipelines, implement infrastructure as code with Terraform and ARM/Bicep, monitor cloud services, troubleshoot performance, and support AI/ML workloads on Azure ML. Collaborate with development, data science, and security teams while managing Azure services, storage, clusters, networking, microservices, and compliance in an agile environment.

Design user-centered digital services through research, service design, interaction design, journeys, flows, prototypes, interfaces, and design specifications. Collaborate with users, stakeholders, researchers, engineers, and multidisciplinary teams to create accessible, inclusive solutions. Lead workshops, evaluate designs, contribute to design systems, shape user stories and acceptance criteria, and support delivery from discovery through implementation. The role requires at least three years of design experience, a relevant degree, and a portfolio.

Design, develop, test, integrate, and support custom software solutions across multiple applications and system components. Translate requirements into detailed designs, implement applications using React.js and Spring Boot, support production releases, collaborate across teams, and contribute to technical decisions and software architecture.

Supports risk engineering and insurance underwriting by analyzing risk data, preparing BI reports, synthesizing information, and providing risk mitigation guidance. The role requires familiarity with casualty insurance, health and safety, environmental practices, Excel, Power BI, and Salesforce. Work is conducted as an individual contributor under supervision and may involve rotational shifts.

Lead the design, configuration, integration, and release management of Microsoft Dynamics 365 ERP and SaaS solutions. Establish platform standards for stability, performance, and business alignment; analyze complex requirements, troubleshoot functional issues, coordinate across teams, make technical decisions, monitor project progress, and mentor team members.

Leads quality engineers and develops end-to-end testing strategies across the application lifecycle. Oversees test execution, defect resolution, quality metrics, and process improvement. Collaborates across multidisciplinary teams, makes team-level decisions, provides solutions, and mentors junior engineers. Requires expertise in Selenium with Java, automated and API testing, Cucumber BDD, Jenkins CI/CD, test planning, defect tracking, and quality assurance methodologies.

Leads the design, development, testing, deployment, and maintenance of enterprise full-stack applications using .NET, C#, frontend frameworks, APIs, microservices, SQL Server, and Azure. Guides developers through code reviews, engineering standards, debugging, performance optimization, and secure design. Owns DevOps readiness, CI/CD adoption, containerization, and production deployment quality while partnering with architects, stakeholders, and RDE teams to deliver scalable technical solutions.

Analyze and improve client business processes by identifying inefficiencies, designing optimized workflows, and developing transformation roadmaps using digital, AI, automation, and agentic technologies. Build business cases, requirements, and proposals; advise clients on technology-enabled solutions; collaborate with stakeholders; and support business development. The role requires BPM expertise, process improvement experience, ERP knowledge, and consulting experience.

Leads the design, development, integration, testing, and deployment of Python-based Agentic AI solutions. Owns agent orchestration, tool calling, RAG, vector search, LLM patterns, enterprise integrations, cloud and DevOps readiness, observability, testing, responsible AI, security, and compliance. Evaluates AI frameworks, supports production deployment, coaches junior engineers, reviews technical designs and code, and enables cross-functional RDE teams.