Cloud Engineer

Accelerant

7d•Remote

About The Position

We are seeking an experienced Senior Cloud Engineer to join our Technology Services team. This role is at the heart of designing, implementing, and managing secure, scalable, and highly resilient cloud infrastructure across Azure and AWS. You will define technology direction, lead large and complex projects end-to-end, and collaborate with development teams, architects, and business stakeholders to deliver cloud solutions that power a broad range of technology initiatives — including AI-driven platforms, containerized applications, and enterprise data workloads. Experience in the Insurance or Financial Services industry is a plus, but strong technical depth and a continuous improvement mindset are what matter most.

Requirements

Bachelor’s degree in Information Technology, Computer Science, Software Engineering, or equivalent combination of education and experience.
10+ years of overall IT experience, with 5+ years as a cloud or infrastructure engineer in production environments.
Proven hands-on experience designing, implementing, and supporting cloud solutions in Azure and AWS; GCP experience a plus.
Demonstrated ability to lead large, complex technology projects across diverse technologies and cross-functional teams with minimal supervision.
Deep expertise with core cloud services across Azure and AWS: compute, networking, storage, identity/IAM, security, managed Kubernetes (AKS/EKS), and data platform services.
Strong background in Linux and Windows system administration.
Deep experience with networking and security concepts in large-scale, production cloud environments including VNets, VPCs, NSGs, firewalls, private endpoints, and zero-trust access patterns.
Hands-on experience with containerization and microservices: Docker, Kubernetes, and managed Kubernetes services (AKS and/or EKS) in production environments.
Terraform expertise is required — candidates must demonstrate hands-on experience authoring, managing, and scaling IaC in production multi-cloud environments.
Multi-year hands-on AI experience, including deep understanding of AI platforms such as Claude (Anthropic) and ChatGPT (OpenAI), and practical experience building and supporting AI-powered applications.
Experience building and supporting applications developed using AI-assisted development platforms such as Claude Code, Replit, Vercel, or similar rapid-development tooling.
Strong operational experience defining and documenting processes for cloud monitoring, alerting, and infrastructure management.
Experience developing infrastructure architecture documentation and InfoSec/audit deliverables.
Demonstrated ability to work effectively within large, cross-functional teams with strong communication skills.

Nice To Haves

Cloud certifications: Azure (AZ-104, AZ-204, AZ-303, AZ-400) and/or AWS (Solutions Architect, DevOps Engineer, or equivalent) preferred, not required.
Supplemental IaC tooling: familiarity with cloud-native tools such as Azure Bicep, AWS CloudFormation, or AWS CDK is a plus.
CI/CD tooling: Azure DevOps, GitHub Actions, AWS CodePipeline, or similar.
Relational and NoSQL databases: MS SQL Server, Cosmos DB, PostgreSQL.
Observability and monitoring platforms: Datadog experience strongly preferred, including infrastructure monitoring, APM, log management, and alerting across multi-cloud environments.
Background in the Insurance or Financial Services industry.

Responsibilities

Design, implement, and manage secure, scalable, and highly resilient cloud infrastructure across Azure and AWS.
Define technology direction for cloud solutions and drive end-to-end implementation across teams.
Collaborate with development teams, cloud architects, and product teams to architect solutions for complex, enterprise-scale projects.
Configure and administer virtual networks, VMs, and web application hosting environments.
Develop and maintain infrastructure-as-code (IaC) using Terraform to enforce consistency and repeatability across cloud environments.
Lead large, complex technology projects spanning diverse technologies and multiple cross-functional teams.
Define project schedules, milestones, and priorities based on high-level business objectives; manage execution with minimal supervision.
Serve as a results-driven technical lead who can independently drive initiatives from concept through delivery.
Communicate project status, risks, and decisions clearly to stakeholders at all levels.
Design, implement, and operate container-based infrastructure and managed Kubernetes environments across Azure and AWS (AKS, EKS), including cluster lifecycle management, scaling, and capacity planning.
Architect and support microservices solutions leveraging Docker and Kubernetes, applying best practices for service decomposition, inter-service communication, and API gateway integration.
Design and manage container registries and image pipelines across platforms (Azure Container Registry, Amazon ECR) including vulnerability scanning, image versioning, and promotion workflows.
Implement and manage serverless container services (Azure Container Apps, AWS Fargate, AWS Lambda container images) for event-driven and workload-appropriate deployment patterns.
Define and enforce container security standards including network policies, pod security, secrets management (Azure Key Vault, AWS Secrets Manager), and runtime protection.
Integrate container workloads with cloud-native networking, load balancing, and ingress services across both platforms (Azure Application Gateway, AWS ALB/NLB).
Support CI/CD pipeline integration for containerized application builds, testing, and automated deployment to non-production and production environments.
Establish and maintain observability practices for containerized workloads including logging, metrics, and distributed tracing across Azure Monitor, AWS CloudWatch, and third-party tooling.
Bring multi-year, hands-on AI engineering experience to the design, build, and ongoing operation of enterprise-grade AI solutions and platforms.
Deep working knowledge of AI technologies and platforms including Claude (Anthropic) and ChatGPT (OpenAI), including API integration, prompt engineering, and enterprise deployment patterns.
Design and support infrastructure for AI-powered applications built with modern development tools such as Claude Code, Replit, and Vercel.
Support AI and data platform workloads across Azure (Databricks, Data Factory, Azure OpenAI) and AWS (SageMaker, Bedrock) environments.
Contribute to the architecture and operational management of enterprise AI platforms, ensuring performance, availability, and security.
Create and maintain cloud security strategies, policies, procedures, and supporting documentation.
Develop and maintain infrastructure architecture, audit, and InfoSec documentation in line with regulatory and business requirements.
Ensure compliance with standard business practices, industry best practices, and applicable regulatory frameworks (particularly relevant in Insurance/FinServ contexts).
Implement and enforce security controls across cloud environments including identity, networking, and data protection layers.
Define and document operational processes around cloud monitoring, alerting, and infrastructure management.
Provide technical support and issue resolution for cloud-hosted environments.
Lead root cause analysis (RCA) for critical outages and incidents; engineer and implement permanent solutions.
Maintain accurate and auditable records of incident resolutions, configuration changes, and operational decisions to support compliance and knowledge continuity.
Drive a culture of continuous improvement through proactive monitoring, automation, and operational refinement.
Provide technical guidance and mentorship to less experienced team members.