Job Title : AI / ML Agent Developer
Location : All EXL Locations
Department : Artificial Intelligence & Data Science
Position Summary :
We are seeking an experienced and innovative AI / ML Agent Developer to design, develop, and deploy intelligent agents within a multi-agent orchestration framework. This role involves building autonomous agents that leverage LLMs, reinforcement learning, prompt engineering, and decision-making strategies to perform complex data and workflow tasks. You’ll work closely with cross-functional teams to operationalize AI across diverse use cases such as annotation, data quality, knowledge graph construction, and enterprise automation.
Key Responsibilities :
- Design and implement modular, reusable AI agents capable of autonomous decision-making using LLMs, APIs, and tools like LangChain, AutoGen, or Semantic Kernel.
- Engineer prompt strategies for task-specific agent workflows (e.g., document classification, summarization, labeling, sentiment detection).
- Integrate ML models (NLP, CV, RL) into agent behavior pipelines to support inference, learning, and feedback loops.
- Contribute to multi-agent orchestration logic including task delegation, tool selection, message passing, and memory / state management.
- Collaborate with MLOps, data engineering, and product teams to deploy agents at scale in production environments.
- Develop and maintain agent evaluations, unit tests, and automated quality checks for reliability and interpretability.
- Monitor and refine agent performance using logging, observability tools, and feedback signals.
Required Qualifications :
Bachelor’s or Master’s in Computer Science, AI / ML, Data Science, or related field.3+ years of experience in developing AI / ML systems; 1+ year in agent-based architectures or LLM-enabled automation.Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit-learn).Experience with LLM frameworks (LangChain, AutoGen, OpenAI, Anthropic, Hugging Face Transformers).Strong grasp of NLP, prompt engineering, reinforcement learning, and decision systems.Knowledge of cloud environments (AWS, Azure, GCP) and CI / CD for AI systems.Preferred Skills :
Familiarity with multi-agent frameworks and agent orchestration design patterns.Experience in building autonomous AI applications for data governance, annotation, or knowledge extraction.Background in human-in-the-loop systems, active learning, or interactive AI workflows.Understanding of vector databases (e.g., FAISS, Pinecone) and semantic search.