Senior AI Engineer
- Source: Naukri
- Epam Systems
- On-site
- Bengaluru
- Full-Time
- Senior
Job Description
We are seeking a talented and driven Senior AI Engineer to join our team and lead the development of cutting-edge AI/ML models and GenAI solutions. This role offers an exciting opportunity to collaborate across functions and create innovative systems that solve real-world business problems.
Responsibilities
- Build and deploy scalable AI/ML models and GenAI solutions in production
- Design and maintain robust ETL pipelines and data workflows
- Develop LLM-based applications using modern frameworks
- Implement prompt engineering techniques for optimized AI outputs
- Deploy models via APIs and integrate with enterprise applications
- Ensure end-to-end ownership, including development, deployment, monitoring, and optimization
- Collaborate with cross-functional teams to deliver business-driven AI solutions
Requirements
- 5-8 years of general IT experience
- 5+ years of experience in AI Engineering
- Strong programming skills in Python
- Hands-on experience with ETL and data pipelines
- Experience with ML/DL frameworks: TensorFlow, PyTorch, Scikit-learn
- Experience in prompt engineering and working with LLMs
- Familiarity with LLM frameworks: LangChain, LlamaIndex, Hugging Face
- Cloud experience working with Azure, AWS, or GCP
- Experience with MLOps tools such as MLflow, Kubeflow, and Airflow
- Strong experience in API development and model deployment
- English level of minimum B2 (Upper-Intermediate) for effective communication
Nice to have
- Experience with RAG architectures and vector databases
- Knowledge of real-time or streaming data pipelines
- Exposure to scalable system design and microservices architecture
- Familiarity with Databricks and PySpark
- Experience with cloud data solutions and ETL pipelines
Skills
- Python
- Tensorflow
- PyTorch
- Scikit-learn
- LangChain
- LlamaIndex
- hugging-face
- microsoft-azure
- amazon-web-services
- google-cloud-platform
- ml-flow
- mlflow
- kubeflow
- Airflow
- apache-airflow
- azure-databricks
- databricks
- pyspark
