Full Job Description
Onsite Role - No C2C, Only W2
Skills Required:
Python, Machine Learning, Data Science, GCP, Big Query
Experience Required:
Engineer 3 Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang. 6+ years in IT; 4+ years in development Experience designing and implementing Agentic AI solutions, multi-step workflows, autonomous agents, and tool-calling architectures. Experience with AI orchestration frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar technologies. Hands-on experience with MLOps tools and platforms including MLflow, Airflow, Vertex AI, SageMaker, Kubeflow, or equivalent solutions. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Familiarity with vector databases, embeddings, Retrieval-Augmented Generation (RAG), and semantic search architectures. Experience working with enterprise-scale data environments, data lakes, and large datasets. Experience optimizing AI systems for scalability, performance, reliability, and cost efficiency. Experience building AI-powered products, dashboards, analytics solutions, or intelligent automation platforms.
Education Required:
Bachelor's Degree
Additional Information:
4 days in the office Python (advanced), SQL Machine Learning & Deep Learning LLMs, Prompt Engineering, RAG, Embeddings Agentic AI / AI Agents / Tool Calling Vector Databases ML Frameworks: Scikit-learn, TensorFlow, PyTorch MLOps: MLflow, Airflow, CI/CD, model deployment & monitoring Cloud: AWS or GCP Docker, Kubernetes API development (FastAPI / Flask) Data pipelines (ETL), data lakes/warehouses Strong system design & production AI experience
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