Sr Platform & DevOps Engineer

Role: Sr Platform & DevOps Engineer Location: US Domestic (Remote) / India Offshore Overview: We are seeking Senior Platform & DevOps Engineers who can own both infrastructure reliability and CI/CD pipeline development. This is a deliberately broad role: engineers are expected to maintain production platform health, build and operate developer tooling, and actively integrate AI capabilities into the platform layer — including Snowflake Cortex, Azure AI Foundry, and LLM API consumption for pipeline automation and observability enrichment. AI-assisted development tooling (GitHub Copilot, Cursor) is expected as part of the standard workflow. Key Responsibilities: Monitor platform health and data feeds daily to ensure continuity and accuracy of operations Respond to system alerts, investigate incidents, and perform root cause analysis to prevent recurrence Architect and implement scalable microservices in Python and Go Design, build, and maintain GitLab CI/CD pipelines with AI-integrated workflow automation Integrate Snowflake Cortex and Azure AI Foundry capabilities into data and platform workflows Manage deployments and operations via Kubernetes CLI and GitOps workflows Integrate with AWS services including S3, Lambda, SQS, and EC2 Implement secure authentication and authorization using EntraID Manage and rotate secrets, credentials, and access keys per security best practices Perform regular patching, upgrades, and maintenance with minimal service disruption Participate in on-call rotations to support production systems Required Qualifications: 6+ years of combined experience in DevOps, Site Reliability Engineering, or platform engineering High-level proficiency in Python and Go Strong experience with Kubernetes CLI, GitOps workflows, and GitLab CI/CD Hands-on experience with Azure and/or AWS cloud services Working knowledge of Snowflake Cortex or equivalent AI/ML-integrated data platform capabilities Familiarity with LLM API consumption and prompt engineering for automation use cases Familiarity with Azure EntraID for identity and access management Active proficiency with AI-assisted development tools (GitHub Copilot, Cursor, or equivalent) Proficiency in Python for data manipulation (Pandas, Snowpark, Polars, or PySpark) Preferred Qualifications: Experience with Helm, Jinja-based templating, and Kubernetes networking Familiarity with Azure AI Foundry and ML model deployment pipelines Experience integrating ML models into cloud-native services Knowledge of observability stacks: Prometheus, Grafana, Splunk Technology Stack: AWS (S3, Key spaces, CloudWatch, Certificate Authority, EC2, shield), Kubernetes, Helm, Istio, Grafana, Splunk, Locust, Java, Spring Boot, GitLab CI/CD, Terraform, Kafka, Snowflake, Snowflake Cortex, Azure AI Foundry, Python, Go