AI Engineer

Direct Responsibilities

The AI Engineer will have following responsibilities: 

• Design and develop end-to-end machine learning and deep learning pipelines.

• Build, fine-tune, and deploy large language models (LLMs) and generative AI solutions.

• Architect scalable AI infrastructure on cloud platforms (AWS, Azure, or IBM IV2).

• Collaborate with product and data teams to translate business needs into AI-driven solutions.

• Monitor model performance, conduct A/B testing, and drive continuous improvements.

• Ensure responsible AI practices including fairness, explainability, and bias mitigation.

Contributing Responsibilities

• Data analysis and preparation: Collect, preprocess, and analyze large datasets to develop and train AI/ML models.

Collaboration with stakeholders: Work with cross-functional teams, including data scientists, product managers, and business stakeholders, to identify business problems and develop AI/ML solutions.

Maintenance and updates: Maintain and update AI/ML models to ensure they remain accurate and effective over time.

Technical & Behavioral Competencies

• Core AI & ML

- Machine Learning, Deep Learning, Supervised/Unsupervised/Reinforcement Learning

- Natural Language Processing (NLP), Computer Vision, Generative AI , MCP protocol 

- TensorFlow, PyTorch, Keras, Hugging Face Transformers, LangChain, LlamaIndex, Langgraph 

- GPT-4, Claude, Gemini or any Open AI API compatible LLM— fine-tuning, prompt engineering, RAG, function calling

- MLflow, Kubeflow, SageMaker, Vertex AI, Docker, Kubernetes, CI/CD pipelines

Specific Qualifications:

• Minimum 5 years of experience along with Bachelor's Degree 

• Prior experience in similar domain.