Al Engineer-with knowledge of creating agents using frontier models 1. Design and develop Al/ML solutions using supervised, unsupervised, deep learning, NLP, time series forecasting, and anomaly detection techniques to address business challenges. 2.

Build Generative

Al applications leveraging LLMs, prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), and Al agent frameworks. 1.

Experience of working for banking domain 2. Develop and maintain end-to-end Al pipelines, covering data ingestion, preprocessing, model training, deployment, monitoring, and continuous improvement.

- Demonstrate solid programming expertise in Python and SQL, with hands-on experience in Ml. libraries such as Scikit-learn, TensorFlow, PyTorch, Hugging Face, Spacy, and NLTK 3.
- Work with large-scale data ecosystems, including ETL processes, data lakes, data warehouses, streaming platforms, and tools like Spark, Databricks, or Microsoft Fabric.
- Implement MLOps best practices,



including CI/CD pipelines, model governance, explainability, monitoring, Docker-based containerization, and Kubernetes orchestration. 6.

Deploy

Al models through APIs and microservices, ensuring seamless integration with enterprise applications, systems, and cloud platforms.

- Utilize cloud-based Al services on Azure or AWS, including platforms such as Azure Machine Learning and Amazon SageMaker.
- Collaborate with business and technology stakeholders to translate business requirements into scalable Al solutions while tracking ROI and value realization.
- Contribute to Al innovation and best practices through reusable frameworks, Al copilots, semantic models, knowledge graphs, LangChain/Semantic Kernel orchestration, and synthetic data techniques

📌 Al Engineer-with knowledge of creating agents using frontier models - 9+ Years (Bengaluru)
🏢 Tek Grove
📍 Bengaluru