Technical Architect
India
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Job Description
Technical Architect
Delhi, Delhi

Job Summary

We are seeking a highly experienced Senior Data Scientist, Machine Learning Engineer with strong exposure in DevOps (ML Platform/ GCP) with 8+ years of experience to drive AI/ML, infrastructure automation, CI/CD, containerization, and ML platform operations on GCP

initiatives for the RAPTOR platform. The role focuses on ML platform engineering, Vertex AI-based solutions, real-time inference, and scalable ML pipelines while supporting platform modernization and AI-driven improvements.
The candidate will work across incident response, request processing, ML platform support, and developer enablement, with a strong focus on Google Cloud Platform (GCP) and Vertex AI ecosystem.

Key Responsibilities

  • Design, build, and maintain scalable ML pipelines and orchestration frameworks using Vertex AI and Kubeflow.
  • Develop and operationalize machine learning models for batch and real-time inference.
  • Manage end-to-end ML lifecycle: data ingestion, training, evaluation, deployment, monitoring, and retraining.
  • Collaborate on platform modernization initiatives and introduce automation across RAPTOR services.
  • Support incident response, root cause analysis, and production troubleshooting for ML systems.
  • Implement monitoring and alerting frameworks for model performance and failures.
  • Develop and manage REST APIs for model integration and platform services.
  • Work on real-time streaming and event-driven ML architectures using Pub/Sub and Dataflow.
  • Provide developer support for RAPTOR platform and GCP tooling.
  • Contribute to self-service AI capabilities and automation/monitoring frameworks.
    Support ML/AI platform operations (Vertex AI, Gemini, inference systems).
  • Build and maintain CI/CD pipelines for ML and platform services
  • Automate infrastructure provisioning using Terraform and Ansible
  • Manage containerized workloads using Docker and Kubernetes
  • Ensure high availability, scalability, and system reliability
  • Support incident response, monitoring, logging, and alerting systems
  • Optimize deployment pipelines for ML models and data workflows
  • Manage IAM roles, service accounts, and access control policies
  • Enable self-service operations and automation frameworks

Provide platform support to ML engineers and data teams

Skill Requirements

Skills & Qualifications (Categorized)
1. Core ML & Data Science
Skill    Category
ML model development, evaluation, deployment    Must Have
ML pipelines & orchestration (Vertex AI Pipelines / Kubeflow)    Must Have
Real-time inference & streaming ML systems    Must Have
Model monitoring (drift, failure detection, alerting)    Must Have
Feature engineering & model optimization    Good to Have
________________________________________
2. GCP & AI Platform
Vertex AI & ML Platform
Skill    Category
Vertex AI (Batch training, inference, pipelines)    Must Have
Vertex AI Model Monitoring    Must Have
AutoML    Must Have
Gemini / LLM capabilities    Good to Have
________________________________________
3. Data & Processing
Skill    Category
BigQuery (SQL, large-scale data processing)    Must Have
Dataflow (Apache Beam – batch & streaming) (Java SDK)    Must Have
Cloud Composer (Apache Airflow)    Must Have
Google Pub/Sub    Must Have
Cloud Storage (Buckets)    Good to Have
________________________________________
4. Compute & Runtime
Skill    Category
Cloud Run / Cloud Functions    Must Have
App Engine (Flex & Standard)    Must Have
________________________________________
5. Integration & Engineering
Skill    Category
REST APIs development & integration    Must Have
Microservices / service-based architecture understanding    Must Have
Observability (logging, monitoring, tracing)    Must Have
Prompt engineering & evaluation    Good to Have
Google Chat API integration    Bonus
________________________________________
6. Programming & Tools
Skill    Category
Python (primary language, automation scripts)    Must Have
SQL (strong working knowledge)    Must Have
Bash scripting    Must Have
GCP Python client libraries    Must Have
gcloud SDK    Must Have
Java (Apache Beam / Dataflow use cases)    Good to Have

Other Requirements

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Information at a Glance

Why HCLTech?

At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion.