AI Engineer

• Design, develop, and implement machine learning and AI-based solutions.
• Build and optimize Generative AI and LLM-powered applications.
• Develop Retrieval-Augmented Generation (RAG) pipelines and semantic search solutions.
• Work with AI agents, autonomous workflows, and intelligent automation.
• Develop and maintain scalable Python-based applications and APIs.
• Integrate vector databases, embeddings, and external AI services.
• Implement model evaluation, monitoring, and performance optimization.
• Deploy and maintain AI/ML models in production environments.
• Collaborate with cross-functional engineering and product teams.
• Follow best practices for AI security, scalability, reliability, and model governance.

We are looking for an experienced AI/ML Engineer to design, develop, and implement intelligent machine learning and Generative AI solutions. The ideal candidate will have strong hands-on experience in Python, machine learning, Large Language Models (LLMs), and building scalable AI-powered applications.

The individual will work on developing advanced AI solutions, integrating machine learning models into existing applications, and deploying production-ready systems., * 5+ years of experience in AI/ML engineering or related software development.

• Strong programming skills in Python.
• Hands-on experience with Machine Learning and Deep Learning.
• Experience working with LLMs and Generative AI technologies.
• Strong understanding of RAG architecture, embeddings, and semantic search.
• Experience with frameworks such as LangChain, LlamaIndex, or similar.
• Familiarity with vector databases such as Pinecone, FAISS, Chroma, or Weaviate.
• Experience developing REST APIs using FastAPI or Flask.
• Understanding of model deployment, monitoring, and MLOps practices.
• Experience with Docker, Kubernetes, and cloud-based environments.

Preferred Skills

• Experience with AWS, Azure, or Google Cloud.
• Knowledge of MLflow and CI/CD pipelines.
• Experience building enterprise-grade AI applications.
• Knowledge of LLM evaluation, prompt engineering, and AI observability.
• Experience with agentic AI frameworks and multi-agent systems.