Job Summary:

We are seeking a highly skilled Senior AI Engineer to design, develop and deploy advanced Artificial Intelligence and Machine Learning solutions. The ideal candidate should have strong experience in developing AI-driven applications, building and deploying machine learning models, working with Large Language Models (LLMs), and implementing Generative AI solutions.

The candidate will be responsible for developing scalable AI systems, optimizing model performance and collaborating with cross-functional teams to integrate AI capabilities into business applications.

Key Responsibilities:

- Design, develop and deploy AI/ML models for real-world business applications.

- Build and implement Generative AI solutions using Large Language Models (LLMs).

- Develop AI-powered applications using Python and modern AI frameworks.

- Work with LLMs such as GPT, Llama, Claude and other open-source models.

- Develop Retrieval-Augmented Generation (RAG) pipelines and intelligent AI agents.

- Implement prompt engineering, fine-tuning and model optimization techniques.

- Build scalable machine learning pipelines and production-ready AI solutions.

- Work with vector databases such as Pinecone, FAISS, Weaviate and ChromaDB.

- Deploy AI models using cloud platforms such as AWS, Azure or GCP.

- Implement MLOps practices for model deployment, monitoring and lifecycle management.

- Collaborate with product managers, software engineers and data science teams.

- Research emerging AI technologies and recommend innovative solutions.

Required Technical Skills:

- Programming: Python, SQL

- AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn

- Generative AI: GPT, LLMs, LangChain, LangGraph, LlamaIndex

- AI Concepts: NLP, Deep Learning, Machine Learning, Neural Networks

- LLM Techniques: RAG, Fine-tuning, Prompt Engineering, AI Agents

- Vector Databases: Pinecone, FAISS, ChromaDB, Weaviate

- Cloud Platforms: AWS, Azure, GCP

- MLOps: MLflow, Kubeflow, Docker, Kubernetes

- APIs: FastAPI, REST APIs

- Data Engineering: ETL pipelines, data preprocessing and model evaluation

Experience & Qualifications:

- 6 - 11 years of overall experience in software engineering, AI/ML or related domains.

- Minimum 4 - 5 years of hands-on experience in AI/ML engineering.

- Strong expertise in Python and machine learning algorithms.

- Experience developing and deploying production-grade AI solutions.

- Practical experience with LLMs and Generative AI applications.

- Understanding of model evaluation, optimization and scalability.

- Experience working with cloud-based AI infrastructure.

- Strong analytical, problem-solving and communication skills.

- Bachelor's or Master's degree in Computer Science, AI, ML, Data Science or a related discipline.

Preferred Certifications:

- AWS Certified Machine Learning Engineer

- Microsoft Azure AI Engineer Associate

- Google Professional Machine Learning Engineer

- Deep Learning Specialization

- Relevant Generative AI certifications.