Senior AI Engineer
$120,000–$150,000 year
On-site · Bengaluru, Karnataka, India
Job Summary
We are seeking a highly skilled Senior Agentic AI Engineer to design, develop, and deploy production-grade agentic AI systems on Azure cloud infrastructure. Key responsibilities include developing sophisticated agentic AI systems for autonomous decision-making, implementing robust CI/CD pipelines, and optimizing AI agent performance and reliability. The ideal candidate should have extensive experience with Azure services, proficiency in Python and SQL, and a strong background in AI/ML engineering. Qualifications include 3 to 8 years of relevant experience with a focus on autonomous systems, familiarity with machine learning frameworks, and problem-solving skills.
Required Qualifications
- 3 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)
- 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)
- Exceptional analytical and problem-solving skills with ability to debug complex distributed systems
- Strong understanding of software engineering best practices (clean code, design patterns, SOLID principles)
- Experience with monitoring tools (Application Insights, Log Analytics, Grafana)
Desired 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
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