HCLTech
Website:
hcltech.com
Job details:
HCL TECH is hiring for Azure Resident Solution Architect
Years of Experience - 12 to 25 years
Location - Chennai / Bangalore / Hyderabad / Pune / Noida
Key Responsibilities
Architecture & Governance
- Define and evolve the Azure Databricks lakehouse architecture (Delta Lake, Unity Catalog, DLT, Workflows) to meet performance, cost, and compliance objectives; lead standards for versioning, lineage, and access controls.
- Document architecture, workflows, and best practices for knowledge sharing and audit/compliance readiness.
- Provide technical oversight and guidelines across squads; run design reviews, performance clinics, and readiness sessions.
- Partner with security, compliance, and platform teams to embed DevSecOps and data governance across ML/LLM lifecycles.
MLOps & LLMOps (Azure-first)
- Architect and implement end-to-end MLOps/LLMOps pipelines using Azure Machine Learning, Azure OpenAI, Databricks, MLflow, and Azure DevOps (Git, CI/CD), ensuring reproducibility and traceability.
- Design scalable training, deployment, and monitoring architectures for ML and LLMs, including AKS for real-time serving and batch/scoring jobs via Databricks Jobs/Workflows.
- Manage AKS clusters and containerized ML workloads; standardize Docker images, Helm charts, and environment build processes.
- Ensure model governance, versioning, and reproducibility with MLflow (experiments, registry) and Azure DevOps (pipelines, artifacts).
- Promote DevSecOps across the ML lifecycle (secrets management, vulnerability scans, policy as code, gated releases).
- Monitor and troubleshoot production ML/LLM systems for availability, latency, drift, and cost; standardize SLOs and on‑call runbooks.
Collaboration & Delivery
- Collaborate with data scientists and data engineers to streamline feature engineering, experiment management, testing, and release workflows; mentor teams on PySpark/Delta performance tuning and code quality.
- Work with platform and networking teams on workspace setup, clusters/pools, Git integration, and Workflows orchestration; enable blue/green and canary strategies for models and data pipelines.
- Evangelize accelerators and best practices (e.g., automation, data quality validation, CI/CD blueprints) and support demos/PoVs with stakeholders.
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