Data Scientist - Agentic AI Developer
CAI (Computer Aid, Inc.) (company site, opens in a new tab)6–8 yrsOn-siteDirect career pageEst. 28–45 LPA
Posted 12h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop, deploy, and monitor production-ready machine learning, Generative AI, LLM, RAG, and Agentic AI solutions using frameworks like LangGraph, LangChain, and AWS Bedrock Agents.
- Design and implement complex multi-step and multi-agent AI workflows including tool calling, state management, human-in-the-loop processes, retries, and tracing with integration to model control plane (MCP).
- Build secure, scalable AI applications leveraging Databricks Apps, MLflow, APIs, Docker, and AWS cloud services while performing continuous model evaluation and improvement based on business metrics.
Minimum Requirements
- 6 to 8 years of Data Science experience with at least 3 years of hands-on Generative AI development.
- Advanced Python development skills of 5+ years including Pandas, NumPy, PySpark, and SQL.
- Hands-on experience with machine learning and deep learning frameworks such as Scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow.
- Experience with AWS Bedrock, Databricks platform components (MLflow, Vector Search, Model Serving), and container/deployment technologies (Docker, FastAPI, Lambda, API Gateway).
Ideal Candidate Profile
- Proven capability to build complex, end-to-end multi-agent AI systems from first principles beyond AutoML or pre-built models, indicating high technical depth.
- Experience with advanced AI workflows including RAG pipelines, embeddings, hybrid retrieval, prompt engineering, and AI system evaluation metrics (recall@k, MRR, nDCG).
- Comfortable communicating technical trade-offs and data-driven insights to both business and engineering stakeholders in a collaborative environment.