Skills Required

AI AgentsGenerative AI ToolsLangchainLarge Language Models (LLMs)MLOps (Deployment & Monitoring)Model Evaluation & ExperimentationPrompt EngineeringPythonRetrieval-Augmented Generation (RAG)Tool Use / Function Calling

About the Job

We are seeking an experienced AI/ML Engineer to design, build, and deploy intelligent solutions that power modern product experiences. This Full-time role is OnSite and will focus on developing practical, production-ready AI systems—especially AI Agents—using state-of-the-art language and generative AI technologies. You’ll collaborate with cross-functional teams to translate business needs into robust machine learning workflows, iterative prototypes, and scalable services that deliver measurable impact.

Roles & Responsibilities

Design and implement AI agents and agentic workflows that can interpret tasks, call tools, and produce reliable outputs.
Develop end-to-end solutions using Python for data processing, model integration, and application logic.
Build and orchestrate LLM-powered applications with LangChain, including prompt/routing strategies and tool use patterns.
Integrate Generative AI tools and APIs into production systems with strong observability, testing, and performance tuning.
Collaborate on fine-tuning or retrieval-augmented approaches (as needed) to improve quality, relevance, and consistency.
Validate system outputs through automated evaluation and continuous improvement of prompts, pipelines, and model behavior.
Document architecture decisions, workflows, and deployment steps to ensure maintainable engineering practices.
Support deployment and monitoring of AI services to ensure scalability, reliability, and security best practices.

Required Skills & Qualifications

Strong hands-on experience with AI Agents and LLM application development.
Proficiency in Python and experience building production-grade ML/AI components.
Experience developing with LangChain, including chaining, retrieval, tools, and workflow orchestration.
Working knowledge of Generative AI Tools and their safe, effective application in real-world products.
Solid understanding of machine learning concepts and practical model/app integration fundamentals.
Strong problem-solving skills, attention to detail, and ability to iterate quickly based on evaluation results.