Kyndryl
Data&AISpecialist
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“Data & AI Specialist at Kyndryl. Skills: Data engineering, AI engineering, Cloud platforms, MLOps. Build and operationalize scalable data and AI solutions. Translate architectural designs into production-ready systems”
What You'll Achieve.
Unlock the value of their data and AI; Deliver reliable, scalable, and secure solutions; Enable intelligent automation; Enable real-time insights; Enable AI-driven decision-making; Contribute directly to business innovation; Contribute to operational efficiency; Transform enterprise workflows; Transform customer experiences; Shape what's next
Industry & Context.
Analytical and problem-solving skills; Adapt solutions to real-world business challenges
What They're Looking For.
Must Have
2–3 years of experience in data engineering, software engineering, or AI engineering roles, programming skills in experience with C++, C#, or Rust is a plus, Experience with cloud platforms (AWS, Azure, GCP) and cloud-native development, Hands-on experience with data platforms (data lakes, data warehouses, streaming systems), Familiarity with distributed systems, concurrency, and asynchronous programming, Experience with containerization (Docker) and orchestration concepts, Knowledge of API design, authentication, and secure execution environments, Exposure to MLOps practices, model deployment, and monitoring, Familiarity with LLMs, generative AI, and agentic AI concepts
Nice to Have
Experience with AI orchestration frameworks and agent-based systems, Exposure to vector databases, semantic search, and retrieval-augmented generation (RAG) patterns, Experience working in agile/startup-like environments with rapid MVP delivery, Participation in digital transformation or AI-native product development initiatives, analytical and problem-solving skills
What You'll Do.
Build and operationalize scalable data and AI solutions
Translate architectural designs into production-ready systems
Work on cloud-native platforms
Develop and maintain data pipelines
Maintain AI-enabled services
Implement and integrate machine learning solutions
Integrate LLM-powered solutions
Contribute to real-time data architectures
Contribute to batch data architectures
Support MLOps practices
Manage model versioning
Manage model deployment
Manage model monitoring
Manage model lifecycle
Build services for AI applications
Build services for data applications
Contribute to containerized deployments
Contribute to orchestrated deployments
Work in agile development environments
Manage CI/CD pipelines
How You'll Work.
Team & Collaboration
Collaborate with solution architects; Collaborate with data scientists; Collaborate with software engineers; Work across teams; Communicate technical concepts clearly
Communication Scope
Communicate technical concepts clearly
Process & Methodology
Agile development environments, Rapid MVP delivery
Full Job Description
**Who We Are** At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. **The Role** **The Role** As an AI & Data Engineer, you will build and operationalize scalable data and AI solutions by translating architectural designs into production-ready systems. You will work on cloud-native platforms, modern data infrastructures, and AI-driven applications, including generative and agentic AI, supporting the full lifecycle from prototype to deployment. You will: * Develop and maintain data pipelines and AI-enabled services using cloud-native technologies. * Implement and integrate machine learning and LLM-powered solutions within enterprise workflows. * Contribute to real-time and batch data architectures (data lakes, streaming platforms, event-driven systems). * Support MLOps practices, including model versioning, deployment, monitoring, and lifecycle management. * Collaborate with solution architects, data scientists, and software engineers to deliver MVPs and production solutions in fast, iterative cycles. * Build secure, scalable APIs and services for AI and data applications. * Contribute to containerized and orchestrated deployments (Docker, Kubernetes). * Work in agile development environments, managing pull requests, code reviews, and CI/CD pipelines. **Your Impact** You will help organizations unlock the value of their data and AI by delivering reliable, scalable, and secure solutions. Your work will enable intelligent automation, real-time insights, and AI-driven decision-making, contributing directly to bu
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