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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and managing scalable deployment pipelines for AI models, with a strong focus on cloud infrastructure, CI/CD automation, and security protocols. Proficient in collaborating with cross-functional teams to ensure ethical AI practices and maintain system health.
Highest-signal resume keywords
MLOpsDevOpsGCPAWSPython
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
MLOpsDevOpsPythonBashTerraformDockerKubernetesAI/ML Orchestration ToolsMonitoring LLM ExecutionData Drift Tracking
Soft Skills
Advanced English Communication
Tools & Technologies
LangGraphCrewAIN8nLangtraceAgentOpsPrometheusCloudWatchGrafanaVertex AISageMaker
Industry Keywords
Cloud Security ProtocolsData PrivacyEthical AI PrinciplesBias DetectionExplainabilityCompliance
Tech Stack
Tools & technologiesAmazon RedshiftAWSBigQueryCloudDockerGoogle Cloud PlatformGrafanaKubernetesPrometheusPythonPyTorchTerraform
About the role
Key responsibilities & impact- Design, deploy, and manage scalable, production-grade deployment pipelines for autonomous AI models and multi-agent workflows using LangGraph, CrewAI, and n8n
- Build and maintain resilient multi-cloud AI infrastructure on GCP or AWS
- Establish automated CI/CD and Continuous Training pipelines using Git, Docker, and Kubernetes
- Implement observability frameworks using Langtrace, AgentOps, Prometheus, CloudWatch, and Grafana
- Track model drift, latency, and autonomous decision accuracy in real time
- Implement security architectures including IAM, data encryption, prompt injection defense, and automated GDPR safety guardrails
- Establish data quality standards, version control, and ethical AI safeguards
- Collaborate with cross-functional AI teams across the operational lifecycle
Requirements
What you’ll need- 4+ years of professional experience in MLOps or DevOps
- 1+ year dedicated to deploying, evaluating, and managing production AI/ML models and agentic workflows
- Deep hands-on experience with GCP (Vertex AI, Cloud Storage, BigQuery, Cloud Functions) or AWS (SageMaker, S3, Redshift, Lambda)
- Proficiency in Python, Bash, Terraform, Docker, Kubernetes, and AI/ML orchestration tools (PyTorch, LangGraph, CrewAI, n8n)
- Hands-on expertise monitoring LLM execution, tracking data drift, and maintaining system health using tools like Langtrace, AgentOps, Prometheus, or CloudWatch
- Solid understanding of cloud security protocols (IAM, data privacy) and ethical AI principles (bias detection, explainability, compliance)
- Advanced English skills, written and spoken, mandatory for collaboration with U.S.-based teams across East/West Coast time zones
Benefits
Comp & perks- Competitive Pay (USD)
- Holidays Off & Paid Time Off
- Health insurance assistance program
- 100% Remote
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks
- Agentic AI tools and training
- Coursera Enterprise
- Studio practice labs
- L1-L7 Career Framework
- High-touch onboarding
- Transparent leadership communication
- Community recognition
- Psychological safety
- Continuous multi-project pipeline
- Direct engagement with U.S. client teams and roadmaps