About the Role :

We are looking for a talented AI Engineer to design, develop, and deploy AI/ML-powered solutions that enhance business capabilities, automate processes, and improve customer and employee experiences. The ideal candidate should have strong expertise in Machine Learning, Large Language Models (LLMs), Generative AI, Data Engineering, and Cloud Platforms, with experience building production-ready AI applications.

Key Responsibilities :

AI & Machine Learning Development :

- Design, develop, and deploy Machine Learning and Generative AI solutions.

- Build applications using LLMs, embeddings, transformers, and Retrieval-Augmented Generation (RAG) architectures.

- Develop scalable AI services and microservices using Python, REST APIs, and cloud-native technologies.

- Optimize AI models for performance, accuracy, scalability, and cost efficiency.

Data Engineering :

- Work with structured and unstructured datasets for feature engineering, vectorization, and model training.

- Build and maintain data pipelines for training, validation, and inference.

- Collaborate with Data Engineering teams on data ingestion, storage, and governance.

MLOps & Model Deployment :

- Implement CI/CD pipelines for ML model deployment.

- Monitor model performance, drift, and retraining strategies.

- Manage model lifecycle, observability, logging, and monitoring.

AI Architecture & Integration :

- Integrate AI solutions with enterprise applications and cloud platforms (Azure, AWS, or GCP).

- Build RAG solutions using vector databases such as Pinecone, FAISS, Weaviate, or Azure AI Search.

- Ensure AI solutions comply with enterprise security, governance, and ethical AI standards.

Collaboration :

- Partner with Product Managers, Engineers, and Business stakeholders to translate business requirements into AI solutions.

- Conduct Proof of Concepts (POCs), demos, and technical solution discussions.

- Explain AI capabilities and limitations to both technical and non-technical stakeholders.

Required Skills :

Technical Skills :

- Strong proficiency in Python with libraries such as NumPy, Pandas, PyTorch, TensorFlow, and Hugging Face Transformers.

- Hands-on experience with Generative AI and Large Language Models (OpenAI, Azure OpenAI, Anthropic, Llama, etc.).

- Strong understanding of Machine Learning, NLP, Deep Learning, and Vector Embeddings.

- Experience with Azure, AWS, or GCP cloud platforms.

- Knowledge of MLOps tools such as MLflow, Kubeflow, Azure ML, SageMaker, or Databricks.

- Experience with Vector Databases including Pinecone, Chroma, FAISS, and Azure AI Search.

- Familiarity with Docker and Kubernetes.

Preferred Qualifications :

- Experience designing production-scale AI applications.

- Knowledge of scalable AI architecture and cloud-native deployment.

- Strong analytical, problem-solving, and communication skills.