Kyndryl

Platform Engineer

• Translate business challenges into target-state cloud platforms across Azure, GCP, and AWS
• Build enterprise Kubernetes container platforms and GitOps-based delivery with ArgoCD
• Build self-service developer environments and secure landing zones
• Support platforms hosting and serving generative AI systems, including LLM hosting, LLM gateways, and agentic workflows
• Own end-to-end delivery by building CI/CD pipelines and implementing Infrastructure as Code with Terraform and Helm
• Guide legacy application modernisation, microservices migrations, and API integrations
• Implement end-to-end platform security, including CI/CD security tooling, Kubernetes segmentation, managed identities, and secure access controls
• Manage SSL/TLS certificate lifecycles, DNS zones, and secure network access to endpoints
• Define architectural standards and guardrails using policy-as-code, OPA, access controls, secrets management, and compliance-driven engineering
• Instrument platforms for observability with Grafana, Prometheus, and OpenTelemetry
• Capture deployment learnings and share best practices with core platform teams
• Contribute code, automated blueprints, and feedback to core platform teams
• Own solution design and deployment for cloud platform and infrastructure modernisations
• Collaborate with AI engineers to integrate platform and agentic AI workstreams

Forward Deployed Engineer – Platform Engineer

• Own architectural direction and delivery for major digital transformation programmes
• Align enterprise goals with target-state cloud architectures
• Guide technical direction and partner with AI engineers
• Design and build target-state cloud platforms across Azure, GCP, and AWS
• Establish enterprise container platforms using Kubernetes and GitOps delivery with ArgoCD
• Build self-service developer frameworks and landing zones using Terraform and Helm
• Architect platforms hosting and serving generative AI systems, including LLM hosting, gateways, and agentic workflows
• Guide legacy application modernisation, microservices migrations, and API integrations
• Implement end-to-end platform security, including CI/CD tooling, Kubernetes segmentation, managed identities, access controls, secrets management, and compliance engineering
• Own connectivity and network-level security, including SSL/TLS certificates, DNS zones, and secure endpoint access
• Define architectural standards, guardrails, policy-as-code, and governance controls
• Instrument platforms for observability using Grafana, Prometheus, and OpenTelemetry
• Provide architectural oversight across multidisciplinary workstreams and unblock teams directly
• Capture field learnings, codify reusable patterns and blueprints, and mentor engineers hands-on
• Translate enterprise requirements into technical roadmaps for senior stakeholders

Lead Platform Engineer, Forward Deployed

AI Engineer

• Connect customer business needs directly to IT strategy
• Design agile, sustainable and flexible solutions with AI at the core
• Develop high-level, enterprise-wide architecture aligned with business missions
• Apply industry knowledge and best practices to develop modern IT solutions
• Understand customer needs and constraints to build high-performance frameworks
• Provide expert direction on Kyndryl solutions and industry strategies
• Align IT infrastructure with the customer's business landscape
• Influence customers and drive adoption of leading-edge solutions
• Tailor strategies to customers' industries and business landscapes
• Collaborate with IT professionals to build digital solutions
• Communicate effectively with customers and sell technology solutions

AI & Platform Factory Architect

• Own delivery of AI applications for complex customer engagements
• Translate business challenges into agentic AI applications and generative AI use cases
• Build and iterate agentic workflows, RAG pipelines, and LLM API integrations
• Process unstructured data into condensed, structured knowledge, including ontology extraction
• Write production-grade Python services with FastAPI
• Apply design, testing, code review, and CI/CD practices
• Work with relational and graph databases to model and serve data behind AI applications
• Collaborate with platform engineering throughout hosting and MLOps/LLMOps deployment
• Define AI governance and responsible-use guardrails, including data privacy boundaries and OPA/Rego policy enforcement
• Instrument AI applications for observability using OpenTelemetry and Prometheus
• Guide clients through legacy modernisation into AI-enabled workflows
• Troubleshoot performance and reliability issues
• Capture deployment learnings and share best practices with core AI platform teams
• Contribute code, reusable agentic patterns, and feedback to core platform teams

Forward Deployed Engineer – AI, Agentic Engineer

DevOps Engineer

• Work on large enterprise, fast-track infrastructure projects
• Define sourcing strategies and select providers aligned with customers’ IT and automation strategies
• Deliver highly complex, multi-disciplined consulting engagements
• Prioritize use cases and conduct ROI and business case analyses
• Incorporate security and resiliency into future-state designs
• Develop future-state visions and roadmaps
• Define infrastructure and network requirements for IT and business needs
• Identify opportunities to optimize efficiency, minimize costs, reduce risks, and enhance performance
• Capture, prioritize, and analyze functional and non-functional technical requirements
• Shape the evolution of intellectual capital assets
• Contribute to the development of practice resources
• Collaborate with Consultants, Architects, Project Managers, and cross-functional Technical Subject Matter Experts

• Own the technical direction and delivery of major enterprise AI programmes
• Architect agentic systems and generative AI applications for production
• Collaborate closely with platform engineering throughout design, build, and deployment
• Align enterprise goals with target-state AI architectures for senior stakeholders
• Guide the team’s technical direction while remaining hands-on
• Design and build agentic AI applications, multi-agent workflows, and supporting frameworks
• Build RAG pipelines and integrate LLM APIs, vector databases, and MCP tooling
• Process unstructured data into condensed, structured knowledge, including ontology extraction
• Write production-grade Python services with FastAPI
• Work with relational and graph databases to model and serve data behind AI applications
• Support hosting, scaling, MLOps, and LLMOps in collaboration with platform engineering
• Define AI governance and responsible-use guardrails
• Instrument AI applications for production observability
• Translate enterprise requirements into AI solution roadmaps
• Capture field learnings and codify reusable agentic patterns
• Mentor engineers hands-on
• Provide architectural oversight across multidisciplinary workstreams

Lead AI Engineer, Forward Deployed

• Unite and guide stakeholders from clients, governance, project executives, delivery teams, and vendors
• Understand project requirements and determine the best technical solution
• Consult with clients, gather inputs, and understand solution needs
• Define how Kyndryl can meet client requirements
• Design appropriate technical solutions
• Lead technology implementation
• Support projects from initiation through delivery
• Deliver products on time and within budget
• Work across major cloud platforms and engage subject matter experts when needed
• Influence, create, and deliver solutions from start to finish

Senior Platform Engineer – Agentic AI, Harness Engineering

QA Engineer

• Design, build, and maintain high-volume business logic running on mainframes
• Refactor legacy code so modern cloud and mobile applications can interact with mainframe core data
• Monitor architecture and identify opportunities to optimize code and maintain or enhance mainframe performance
• Debug, troubleshoot, and analyze complex system interactions
• Extract business logic from legacy systems for migration or integration with cloud-based services
• Collaborate with a global community of experts on mainframe modernization