Artificial Intelligence Engineer

Job Summary
We need an AI Engineer who can independently design and deliver production-grade AI/ML solutions, from requirements and data preparation through deployment, monitoring and continuous improvement, working closely with US business and technology teams across time zones.

Role : Consultant/Contractual

Key Responsibilities

• Design, build and deploy end-to-end LLM and ML solutions (RAG, agents, NLP, classification, forecasting, recommendation, document processing)
• Architect and build agentic AI systems: autonomous and multi-agent workflows with tool calling, memory, planning and human-in-the-loop controls
• Perform data preprocessing, feature engineering, model training and performance tuning
• Build and maintain scalable data pipelines and backend APIs using Python Django (Django REST Framework), and FastAPI/Flask where suitable, and integrate ML services with enterprise systems
• Translate business problems into AI solution designs; present working demos and results to stakeholders
• Implement evaluation, monitoring, explainability, guardrails and cost controls for AI workloads
• Set up MLOps practices: experiment tracking, model/data versioning, CI/CD, containerization, and reproducible deployments on cloud platforms
• Document model architectures, design decisions and deployment processes
• Mentor junior engineers, perform code reviews and contribute to team best practices

Required Skills

• 3+ years of hands-on experience with Python and ML/AI engineering, including strong Django experience
• Solid grounding in ML and deep learning frameworks (PyTorch, TensorFlow, scikit-learn, Hugging Face)
• Practical experience building agentic AI solutions (agent frameworks such as LangGraph, CrewAI, AutoGen or similar; tool calling; orchestration)
• Hands-on experience delivering LLM/GenAI applications to production (RAG, embeddings, prompt design, vector databases)
• Experience with cloud AI/ML services (Azure OpenAI / Azure ML / AWS Bedrock / SageMaker)
• Strong SQL and API design skills; working knowledge of NoSQL databases
• Docker, Git and CI/CD; working knowledge of Kubernetes
• Understanding of model evaluation, monitoring and responsible AI practices