Senior Quality Assurance Engineer

Ecolab Food Safety & Hygiene Solutions Private Limited

Bengaluru

On-site

INR 4,000,000 - 7,000,000

Full time

9 days ago
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Job summary

Ecolab Food Safety & Hygiene Solutions Private Limited in Bengaluru seeks a Senior AI Engineer to design, develop, and deploy production-grade agentic AI systems on Azure cloud infrastructure. The role focuses on autonomous agents, robust CI/CD pipelines, and scalable data processing workflows.

The ideal candidate has 5–8 years in AI/ML with 2+ years in agentic AI, strong Python/SQL skills, and hands-on Azure Databricks experience. Collaborative, security-conscious, and able to mentor juniors.

Qualifications

  • 5–8 years in AI/ML engineering with at least 2+ years in agentic AI/autonomous systems
  • Proficient in Python and SQL
  • Deep understanding of Azure cloud services (Functions, OpenAI, ML, App Services, Storage, Key Vault)
  • Hands-on Azure Databricks for large-scale data processing and ML workflows
  • Proven track record deploying/maintaining AI systems in production
  • Strong experience building CI/CD pipelines (Azure DevOps or GitHub Actions)
  • Proficient with Docker and Kubernetes/AKS

Responsibilities

  • Design autonomous agentic AI systems capable of decision-making and task execution
  • Architect and implement production-grade AI solutions on Azure services
  • Build and maintain CI/CD pipelines for automated testing and deployment
  • Develop scalable data processing workflows using Azure Databricks and Spark
  • Implement testing strategies for AI applications and monitor performance
  • Mentor junior engineers and lead AI architecture discussions
  • Collaborate with cross-functional teams to integrate AI agents
  • Implement security practices including Key Vault integration and RBAC

Skills

Python
SQL
Azure
CI/CD
Docker
Kubernetes
Azure Databricks

Tools

Azure DevOps
GitHub Actions
Azure Functions
Azure ML

Job description

Senior AI Engineer

We are seeking a highly skilled Senior Agentic AI Engineer to design, develop, and deploy production-grade agentic AI systems on Azure cloud infrastructure. The ideal candidate will have extensive experience building autonomous AI agents, deploying complex AI solutions to production, and implementing robust CI/CD pipelines.

Key Responsibilities
  • Design and develop sophisticated agentic AI systems capable of autonomous decision-making and task execution
  • Architect and implement production-grade AI solutions using Azure services (Azure Functions, Azure OpenAI, Azure Cognitive Services, etc.)
  • Build and maintain CI/CD pipelines using Azure DevOps and/or GitHub Actions for automated testing and deployment
  • Develop scalable data processing workflows using Azure Databricks and Apache Spark
  • Implement comprehensive testing strategies for AI applications including unit tests, integration tests, and performance testing
  • Optimize AI agent performance, reliability, and cost-efficiency in production environments
  • Design and implement monitoring, logging, and observability solutions for AI systems
  • Mentor junior engineers and lead technical discussions on AI architecture and best practices
  • Collaborate with cross-functional teams to integrate AI agents into existing systems
  • Implement security best practices including managed identities, Key Vault integration, and RBAC
Required Skills & Qualifications
Technical Expertise
  • 5 to 8 years of experience in AI/ML engineering with at least 2+ years focused on agentic AI or autonomous systems
  • Expert-level proficiency in Python and advanced knowledge of SQL
  • Deep understanding of Azure cloud services (Azure Functions, Azure OpenAI, Azure ML, App Services, Storage, Key Vault)
  • Extensive hands-on experience with Azure Databricks for large-scale data processing and ML workflows
  • Proven track record of deploying and maintaining AI systems in production environments
  • Strong experience building CI/CD pipelines using Azure DevOps and/or GitHub Actions
  • Proficiency in containerization technologies (Docker, Kubernetes/AKS)
AI/ML Knowledge
  • Strong foundation in Machine Learning, Natural Language Processing, and Deep Learning
  • Experience with large language models (LLMs) and prompt engineering
  • Knowledge of multi-agent systems
  • Understanding of RAG (Retrieval-Augmented Generation) architectures
  • Experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn, Transformers)
Problem-Solving & Quality
  • Exceptional analytical and problem-solving skills with ability to debug complex distributed systems
  • Experience designing and implementing comprehensive test suites for AI applications
  • Strong understanding of software engineering best practices (clean code, design patterns, SOLID principles)
  • Experience with monitoring tools (Application Insights, Log Analytics, Grafana)
Preferred Qualifications
  • Azure certifications (Azure AI Engineer Associate, Azure Solutions Architect)
  • Experience with microservices architecture
  • Knowledge of MLOps practices and tools (MLflow, Azure ML Pipelines)
  • Experience with vector databases and semantic search

Experience Level Senior Level

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