Senior Technical Lead
HCLTech
Bengaluru, Karnataka, IndiaPosted 24 days agoDiscoveredMatch locked
Job Summary
1) Focused on building and evaluating enterprise-scale agentic AI systems.
2) The candidate would assess, prototype, and recommend platforms including Azure AI Foundry, AWS Bedrock/AgentCore, Google Cloud Gemini, Databricks AgentBricks, and TrueFoundry for production adoption.
3) Experience with LLM-based systems — agent workflows, RAG pipelines, and enterprise AI applications Experience Required: 5–8 years
Tech Stack: Azure | Databricks | AKS | ARO | Terraform | MLflow | CI/CD
Role Summary
We are looking for a seasoned cloud engineer to support ML development teams and drive end to end automation for model deployment and operations across Azure, Databricks, and Kubernetes platforms.
Key Responsibilities
Key Responsibilities
- Build and maintain CI/CD/CT pipelines for ML models using Azure DevOps / GitHub Actions/Jenkins
- Develop and manage deployment workflows for:
o Databricks Jobs o MLflow models o Microservices running on AKS / ARO
- Automate infrastructure using Terraform, scripting, and GitOps practices
- Manage and optimize:
o Databricks workspaces o AKS clusters o Networking and model serving environments
- Implement monitoring, logging, and alerting for ML systems and platform reliability
- Collaborate closely with ML engineers, data engineers, and application teams
- Ensure security best practices, governance, and cost optimization across MLOps pipelines
Required Skills
- Strong hands on experience with Azure, AKS, ARO and Databricks
- Solid experience with MLflow, Kubernetes based model deployments
- Proficiency in Python and Bash / PowerShell
- Good understanding of cloud security, networking, and distributed systems
Skill Requirements
Key Responsibilities
- Build and maintain CI/CD/CT pipelines for ML models using Azure DevOps / GitHub Actions/Jenkins
- Develop and manage deployment workflows for:
o Databricks Jobs o MLflow models o Microservices running on AKS / ARO
- Automate infrastructure using Terraform, scripting, and GitOps practices
- Manage and optimize:
o Databricks workspaces o AKS clusters o Networking and model serving environments
- Implement monitoring, logging, and alerting for ML systems and platform reliability
- Collaborate closely with ML engineers, data engineers, and application teams
- Ensure security best practices, governance, and cost optimization across MLOps pipelines
Required Skills
- Strong hands on experience with Azure, AKS, ARO and Databricks
- Solid experience with MLflow, Kubernetes based model deployments
- Proficiency in Python and Bash / PowerShell
- Good understanding of cloud security, networking, and distributed systems
Other Requirements
null
Not included in the source posting: about the role, benefits.
Skills
databricksazuremachine-learningkubernetesartificial-intelligencebashci-cdpythonterraformdevopsgithub-actionsjenkins
Who can apply
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