Cloud Infrastructure & AI Engineer

We’ve come a long way since we first opened our doors, but our mission has always stayed the same: to provide world class solutions for the travel industry. Travel Booster is a constantly improving ERP solution that frees users from the complexities of creation so they can do more, faster. We are looking for a hands‑on engineer to own our cloud infrastructure and CI/CD pipelines on AWS with Azure DevOps (Pipelines & Releases). You will take over existing infrastructure and pipelines written in PowerShell and Python, stabilize & improve them, and lead AI/LLM enablement across Dev, QA, and Support—including building internal agents, integrating with LLMs (via MCP and other frameworks), and driving AI adoption in day‑to‑day workflows. You’ll partner closely with R&D to streamline builds, deployments, environment management, and observability, while also pushing upgrades and optimizations in AWS services.

What will your job look like?

Key Responsibilities

CI/CD & Cloud Infrastructure

• Own, maintain, and enhance Azure DevOps Pipelines & Releases (multi‑stage YAML/classic) for builds, deployments, and scheduled tasks.
• Refactor existing PowerShell, javascript and Python pipeline scripts for reliability, security, and performance.
• Implement pipeline templates, gates, approvals, artifact versioning, and automated rollbacks.
• Introduce pipeline observability (dashboards, alerts, metrics) and enforce branching, tagging, and release standards.
• Operate and improve AWS environments (Prod/Stage/Dev/QA), including networking, compute, storage, databases, security, and cost management.
• Implement Infrastructure as Code (IaC) (Terraform or AWS CloudFormation); manage parameter stores/secrets.
• Automate environment lifecycle: provisioning, configuration, blue/green & canary releases, and disaster recovery.
• Drive updates and improvements across services (e.g., EKS/EC2/Lambda, RDS/DynamoDB, ElastiCache, S3, CloudFront/ALB/ELB, Route 53, CloudWatch, Systems Manager, IAM, KMS).
• Standardize and automate Dev/QA/SIT/UAT environments; ensure parity with Production where relevant.
• Build ephemeral preview environments per PR; manage test data seeding/anonymization.
• Collaborate with QA to integrate test orchestration (smoke/regression) into pipelines with gates and quality metrics.
• Implement monitoring/alerting (CloudWatch, Prometheus/Grafana), logging (CloudWatch Logs/OpenSearch), and distributed tracing (X-Ray/OpenTelemetry).
• Harden IAM (least privilege, scoped roles), secrets management, key rotation, and compliance checks.
• Track and optimize AWS spend (rightsizing, autoscaling, lifecycle policies).
  
  

• Build and deploy AI-powered features using LLMs (OpenAI, Azure OpenAI, Hugging Face).
• Implement MCP-based integrations for context-aware workflows.
• Design and build internal AI agents (for Dev/QA/Support) to assist with triage, runbooks, test data generation, log analysis, and developer productivity.
• Integrate LLMs via secure patterns (e.g., Model Context Protocol (MCP), retrieval‑augmented generation, prompt engineering, guardrails, and observability).
• Create tooling that plugs AI into pipelines/workflows (PR summaries, release notes, changelog generation, incident post‑mortems).
• Establish data governance for AI: access control, PII handling, prompt/data sanitization, and auditability.
• Write production-grade code for AI workflows, including prompt engineering, function calling, and agent orchestration.
• Integrate AI services into ERP, web apps, and backend systems.
  
  

• 5+ years working with AWS in production (multi‑account, multi‑env).
• 3+ years with Azure DevOps (Pipelines/Releases), including YAML pipelines.
• Strong javascript, PowerShell and Python for automation and pipeline tasks.
• Hands‑on experience with IaC (Terraform or CloudFormation).
• Solid understanding of networking, security (IAM/KMS), containers (Docker; EKS preferred) or serverless (Lambda).
• Experience integrating LLMs/AI into engineering workflows (agents, prompt engineering, RAG, MCP or similar).
• Proven track record of CI/CD best practices, release orchestration, artifact/version management, and rollback strategies.
• Experience with OpenAI/Azure OpenAI, Anthropic, or other LLM providers; familiarity with MCP.
• Knowledge of Node.js build/deploy pipelines (to align with parts of our stack).
• Exposure to C++ build systems (beneficial for our business logic components).
• Observability stack: OpenTelemetry, Grafana, Loki/ELK/OpenSearch.
• Security/compliance tooling (e.g., CIS benchmarks, AWS Config, Inspector).
• Experience with fine-tuning and deploying models in production.
• Excellent interpersonal skills, Proactive, Fast learner and team player
• Knowledge in Agile and Scrum - Advantage
• Excellent English writing and verbal skills – Mandatory