Senior Staff Engineer (Generative AI, Langchain + Langraph, Machine Learning)

Requirements

• 7.5 to 12 years of overall experience in Data Science Machine Learning and Artificial Intelligence.
• Strong hands-on experience with Generative AI fundamentals Large Language Models (LLMs) and Agentic AI systems.
• Proven expertise in developing GenAI applications using LangChain LangGraph and associated ecosystem tools.
• Experience designing and implementing Retrieval Augmented Generation (RAG) solutions including retrieval reranking chunking memory management and context optimization.
• Strong understanding of prompt engineering techniques including instruction tuning ReAct frameworks reasoning strategies planning loops and self-reflection mechanisms.
• Hands-on experience with LLM evaluation frameworks model assessment and GenAI quality measurement methodologies.
• Experience using LangSmith for tracing monitoring debugging evaluation regression testing and performance optimization of GenAI applications.
• Strong knowledge of Vector Databases and Embeddings including FAISS Azure AI Search OpenSearch PGVector or similar technologies.
• Experience building intelligent agents tool-calling agents planner-executor frameworks multi-agent systems and hierarchical agent architectures.
• Good understanding of memory architectures including episodic memory semantic memory and long-term vector-based memory systems.
• Experience integrating AI agents with APIs enterprise applications knowledge repositories and external tools.
• Strong foundation in classical Machine Learning concepts including feature engineering model development hyperparameter tuning and model evaluation.
• Experience working with structured and unstructured datasets for predictive and analytical use cases.
• Understanding of MLOps concepts including model monitoring data drift detection concept drift analysis and model quality management.
• Hands-on experience with cloud platforms such as AWS Azure or Databricks.
• Proficiency with version control systems and collaborative development tools such as Git and GitHub.
• Strong problem-solving analytical communication and stakeholder management skills.
• Candidate should have an official notice period of 30 days or less and must be able to join within one month.

Responsibilities

• Design develop and deploy enterprise-grade Generative AI and Agentic AI solutions using modern LLM frameworks and tools.
• Build scalable GenAI applications leveraging LangChain LangGraph and related ecosystem technologies.
• Design and implement advanced RAG architectures to improve response quality grounding and knowledge retrieval accuracy.
• Develop and optimize prompt engineering strategies to enhance reasoning planning tool usage and response generation capabilities.
• Build intelligent agents capable of tool calling workflow orchestration task planning and autonomous decision-making.
• Develop multi-agent systems and agent collaboration frameworks for complex business workflows.
• Implement memory-driven agent architectures supporting contextual awareness and long-term knowledge retention.
• Create evaluation frameworks to measure performance reliability robustness and business effectiveness of AI solutions.
• Establish monitoring tracing testing and observability frameworks using LangSmith and related tools.
• Build and integrate Model Context Protocol (MCP) based services and external tool integrations.
• Enable AI systems to interact with APIs applications code execution environments and enterprise knowledge sources.
• Apply Machine Learning techniques to solve business problems involving structured and unstructured data.
• Perform model development feature engineering model optimization validation and performance analysis.
• Collaborate closely with engineering architecture and cross-functional teams to productionize AI and ML solutions.
• Ensure scalability security maintainability and reliability of AI-powered applications.
• Support MLOps initiatives including model monitoring drift detection performance tracking and continuous improvement.
• Maintain comprehensive technical documentation coding standards and quality assurance practices throughout the development lifecycle.
• Stay current with emerging trends frameworks tools and best practices in Generative AI Agentic AI Machine Learning and AI Engineering.

Qualifications :

Bachelors or masters degree in computer science Information Technology or a related field.

Remote Work :

No

Employment Type :

Full-time