At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available.
For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries.
As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work!
ABOUT THE ROLE
Mitratech is seeking a senior Site Reliability Engineer III to own and evolve our CI/CD, infrastructure automation, and cloud platform engineering practice. AWS is the primary cloud platform -- you will work daily with a broad AWS service footprint including compute (EC2, Fargate, EKS, Lambda), messaging (SQS), data (RDS, Aurora), AI/ML (Bedrock), analytics (QuickSight), and infrastructure delivery (CDK, Terraform). Azure is a secondary environment you will work in with some regularity; Linux administration underpins everything.
You will be comfortable across all three CI/CD Tools (GitHub Actions, Bitbucket Pipelines, and Jenkins), able to design reusable pipeline patterns, migrate pipelines between tools, and enforce consistent delivery standards regardless of the source control or build platform. Terraform is the primary IaC tool; AWS CDK is used for application-infrastructure co-located patterns and is a key part of this role.
At DevOps III you operate independently on complex problems, make architectural recommendations, mentor junior engineers, and actively raise the bar on delivery reliability and automation coverage. You will also participate in on-call rotation for pipeline and infrastructure events.
A DAY IN THE LIFE
CI/CD Pipeline Engineering — GitHub | Bitbucket | Jenkins
- Design, implement, and maintain end-to-end CI/CD pipelines across GitHub Actions (reusable workflows, composite actions, matrix builds, self-hosted runners), Bitbucket Pipelines (pipe steps, custom runners, deployment environments), and Jenkins (declarative pipelines, shared libraries, agent pools, and Blue Ocean).
- Build reusable pipeline templates and shared libraries that standardize delivery patterns across all three CI/CD platforms -- engineers should be able to ship reliably without knowing which tool runs underneath.
- Drive pipeline governance across all platforms: branch protection policies, PR-required checks, approval gates, environment promotion strategies, and parallel job optimization.
- Implement and enforce pipeline quality gates: automated test integration, SAST/SCA security scanning, container image scanning, Terraform plan validation, CDK diff review, and compliance policy checks.
- Own artifact management across ECR (container images), S3 (build artifacts), and package feeds: versioning strategies, promotion workflows, and retention policies across dev/staging/prod.
- Migrate and consolidate pipelines: when Bitbucket or Jenkins pipelines need to move to GitHub Actions (or vice versa), you design the migration path, execute it, and document the new standard.
AWS Platform Engineering — Core Services (Primary)
- Architect and manage AWS compute services: EC2 (AMI management, launch templates, Auto Scaling Groups), ECS Fargate (task definitions, service discovery, capacity providers), EKS, and Lambda (function packaging, layers, event source mappings, concurrency management).
- Design and maintain AWS messaging and event-driven architectures: SQS (standard and FIFO queues, DLQs, visibility timeouts, batch processing integration), SNS, and EventBridge for decoupled pipeline triggers and async workload patterns.
- Manage AWS data services: RDS and Aurora (multi-AZ, read replicas, parameter groups, automated backups, IAM database authentication, Performance Insights) -- including operational runbooks for failover, patching, and connectivity.
- Own AWS networking design: VPC architecture, subnet strategy, security groups, NACLs, Transit Gateway, VPN/Direct Connect, Route 53, ALB/NLB, PrivateLink, and VPC endpoints for secure private connectivity.
- Manage multi-account AWS Organizations: SCPs, account vending via Control Tower or Account Factory for Terraform, guardrails, and landing zone governance across production, staging, and sandbox environments.
- Implement AWS security posture controls: Security Hub, GuardDuty, Config Rules, CloudTrail, Macie, IAM Access Analyzer, and Secrets Manager -- integrated with CI/CD pipeline policy enforcement.
AWS CDK & Terraform — Infrastructure as Code
- Author and maintain AWS CDK applications (TypeScript or Python) for application-infrastructure co-located patterns: Lambda functions with their event sources, SQS queues, RDS instances, ECS task definitions, and supporting IAM roles -- all as versioned, testable code alongside application code.
- Own and evolve the Terraform/OpenTofu module library for AWS and Azure: design composable modules, enforce DRY principles, manage remote state (S3 + DynamoDB locking), and implement workspace strategies for multi-environment deployments.
- Implement GitOps workflows for all IaC: every resource change goes through PR, plan/diff validation (Terraform plan + CDK diff in pipeline), and pipeline-applied apply/deploy -- zero manual console changes in production.
- Integrate CDK and Terraform into the CI/CD pipeline ecosystem: GitHub Actions workflows for CDK deploy, Bitbucket Pipelines for Terraform apply, and Jenkins shared library steps for IaC validation.
- Manage CDK construct libraries: author reusable L3 constructs that encode Mitratech's opinionated defaults for Lambda, ECS, RDS, and SQS patterns -- reducing boilerplate for product engineers.
AI/ML Operations — AWS Bedrock & Analytics (QuickSight)
- Operate and maintain AWS Bedrock integrations: model deployment automation, inference endpoint configuration, IAM permission boundaries for foundation model access, and Bedrock guardrails for responsible AI use within Mitratech products.
- Build and maintain CI/CD pipelines for Bedrock-enabled applications: package Lambda functions that invoke Bedrock, manage prompt templates and model version configurations as versioned artifacts, and implement canary/blue-green deployment patterns for AI-augmented features.
- Manage QuickSight infrastructure: dataset refresh schedules, capacity management, VPC connectivity for RDS and Redshift data sources, IAM permissions, and embedding configuration for customer-facing analytics within Mitratech products.
- Automate QuickSight asset management: dashboard and dataset deployment via QuickSight APIs integrated into CI/CD pipelines -- no manual dashboard publishing in production.
- Support data pipeline reliability between RDS/Aurora, S3 data lake, SQS-driven ingestion, and QuickSight: monitor data freshness SLAs and integrate pipeline health signals into the team's observability stack.
QUALIFICATIONS
Required
- 5 to 7 years as a DevOps or Cloud/Infrastructure Engineer in production; 4+ years with AWS as the primary platform.
- Hands-on CI/CD expertise across GitHub Actions AND at least one of Bitbucket Pipelines or Jenkins -- must be able to design, build, and maintain pipelines on multiple platforms, not just one.
- AWS CDK proficiency (TypeScript or Python): authoring CDK stacks and reusable constructs for Lambda, ECS Fargate, SQS, RDS, and supporting IAM patterns.
- Expert Terraform: module authoring, remote state (S3 + DynamoDB locking), workspace strategy, and GitOps-driven apply pipelines.
- Deep AWS Fargate: task definition authoring, service auto-scaling, capacity provider strategies, VPC networking, and ECR image lifecycle management.
- AWS Lambda operations: packaging and deployment automation, layers, function URLs, event source mappings (SQS, S3, EventBridge), and concurrency/throttle management.
- AWS SQS: queue design, DLQ configuration, visibility timeout tuning, and batch processing integration with Lambda and Fargate.
- AWS RDS/Aurora: operational runbooks for failover, patching, parameter group management, IAM authentication, and Performance Insights analysis.
- AWS Bedrock: at least one production integration -- model invocation pipelines, IAM permission design, and deployment automation for Bedrock-enabled Lambda functions.
- AWS QuickSight: dataset management, SPICE, VPC connectivity, and API-driven dashboard deployment in CI/CD.
- Strong Linux administration: RHEL/Amazon Linux/Ubuntu OS hardening, systemd, performance profiling, SSM Patch Manager, and Ansible configuration management.
- Shift-left security across all pipeline platforms: SAST, SCA, container scanning, secrets scanning, and IaC security scanning (Checkov, cfn-guard).
Preferred
- AWS certifications: Solutions Architect Professional, DevOps Engineer Professional, or Security Specialty.
- AWS Control Tower / Account Factory for Terraform (AFT) for multi-account landing zone management.
- HashiCorp Vault for dynamic credential issuance and secrets management.
- EC2 Image Builder or Packer for golden AMI pipeline automation.
- AWS Step Functions for complex serverless orchestration patterns alongside Lambda/SQS.
- DORA metrics instrumentation using LinearB, Sleuth, or equivalent engineering productivity platforms.
We are an equal-opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.