• Designing and operating always-on product environments for customer demos, internal use, and stakeholder access • Building feature branch / preview environments to support UX and rapid feedback loops • Enabling internal dogfooding through real, long-running deployments of UDS products • Integrating core system components across Fleet Management, Edge Management, OS, and related services • Reducing reliance on local environments by creating shared, reproducible infrastructure • Supporting pathways toward self-service demo and trial environments • Improve system reliability by enabling continuous, real-world usage and validation • Partnering with engineering, product, and UX to ensure environments reflect real user scenarios

• Own client workstreams independently • Co-lead automation initiatives • Evolve the organisation's automation practice • Deliver high-quality automation solutions across multiple projects • Operate independently in client-facing roles

Role Description Highly skilled Salesforce Agentforce Specialist to lead the design, implementation, and governance of our autonomous AI agents. In this role, you will transform our customer service, sales, and operations by building intelligent agents that do not just chat, but actively execute tasks and workflows. You will bridge the gap between business requirements and technical AI orchestration—leveraging Data Cloud, building precise prompts, and designing multi-agent environments while adhering to strict trust and security standards. Qualifications - Experience in Salesforce Agentforce - Strong understanding of AI orchestration - Ability to design multi-agent environments - Knowledge of Data Cloud - Experience in customer service and sales transformation Requirements - Proven track record in leading design and implementation projects - Ability to work collaboratively with cross-functional teams - Strong analytical and problem-solving skills - Adherence to trust and security standards Benefits - Inclusive workplace culture - Opportunities for personal and professional growth - Commitment to well-being and work-life balance - Equal employment opportunity (EEO) and affirmative action employer

Role Description We are seeking a Senior Platform Engineer who can own infrastructure architecture, reliability, scalability, and platform operations across our cloud environments. This is not a traditional "pipeline management" role. We are looking for someone who can make architectural decisions, evaluate tradeoffs, and build platforms that support large-scale SaaS applications and AI workloads. You will work closely with Engineering, Product, and AI teams to design systems that are secure, resilient, scalable, and cost-efficient. Key Responsibilities - Platform Architecture & System Design - Design and evolve cloud-native platform architecture supporting multi-tenant SaaS applications - Define infrastructure standards, deployment patterns, and platform best practices - Lead architecture reviews and evaluate technical tradeoffs across reliability, performance, security, and cost - Design highly available and fault-tolerant systems across multiple environments - AWS Infrastructure - Architect and manage large-scale AWS environments - Design networking architectures including VPCs, subnets, security groups, routing, load balancing, and connectivity patterns - Build secure deployment architectures aligned with security and compliance requirements - Implement disaster recovery, backup, and business continuity strategies - Kubernetes & Platform Operations - Design and operate production Kubernetes environments - Build scalable container orchestration strategies - Optimize cluster performance, networking, autoscaling, and workload scheduling - Improve developer experience through platform automation and self-service tooling - AI & GPU Infrastructure - Support AI and ML workloads running on AWS - Design infrastructure for model training and inference workloads - Manage GPU provisioning, utilization, scaling, and cost optimization - Collaborate with AI teams to improve deployment and operational efficiency - Reliability & Performance - Define and measure SLIs, SLOs, and operational metrics - Implement monitoring, observability, logging, alerting, and incident management practices - Drive performance optimization and capacity planning initiatives - Lead root cause analysis and reliability improvement efforts - Infrastructure Automation - Build Infrastructure-as-Code solutions using Terraform - Design and optimize CI/CD pipelines - Automate provisioning, deployments, scaling, and operational workflows - Cost Optimization - Continuously evaluate cloud spending - Develop capacity planning models - Balance performance, reliability, and infrastructure costs Qualifications - 6-8 years of experience in DevOps, Platform Engineering, SRE, or Cloud Infrastructure roles. - Proven experience designing and operating production-scale SaaS platforms. - Strong expertise in AWS architecture, networking, security, and deployment strategies. - Deep hands-on experience with Kubernetes, container orchestration, cluster operations, autoscaling, and workload management. - Experience designing highly available, fault-tolerant, and scalable distributed systems. - Strong understanding of system design, architecture trade-offs, and platform scalability. - Hands-on experience with Infrastructure as Code (Terraform preferred). - Experience building and maintaining CI/CD pipelines and deployment automation frameworks. - Strong Linux, networking, and systems engineering fundamentals. - Experience implementing observability, monitoring, logging, and incident management practices. - Experience with disaster recovery planning, backup strategies, and business continuity design. - Experience with cloud cost optimization, capacity planning, and resource utilization management. - Hands-on experience supporting AI/ML workloads in production environments. - Experience designing, provisioning, and operating GPU-based infrastructure for model training and/or inference workloads. - Experience managing and optimizing AWS Bedrock, OpenSearch, and DocumentDB or equivalent platforms. - Strong scripting and automation skills using Python, Bash, or similar languages.