Senior LLM Engineer – GenAI / Machine Learning Job | Python & LangChain

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Senior LLM Engineer – GenAI / Machine Learning Job | Python & LangChain SEO Title: Senior LLM Engineer Job | Generative AI, Python & LangChain Opportunity Meta Description: Explore the Senior LLM Engineer opportunity for experienced AI professionals skilled in Python, LangChain, RAG, machine learning, and cloud platforms. Review job responsibilities, qualifications, and location details. 🚀 Job Overview Are you an experienced software engineer or AI professional with expertise in Generative AI, Large Language Models (LLMs), and machine learning? This Senior LLM Engineer – GenAI / ML opportunity is designed for professionals who can build, deploy, and optimize production-ready AI solutions. The role focuses on developing intelligent systems using Python, LangChain, Retrieval-Augmented Generation (RAG), prompt engineering, and agent-based frameworks. Successful candidates will work with engineering teams and business stakeholders to turn real-world requirements into scalable AI applications. Important location note: The supplied listing specifies India as the work location. Although it is categorized as remote, applicants should confirm whether the position allows remote work from outside India before applying. 📌 Job Details - Job Title: Senior LLM Engineer – GenAI / ML - Category: Software Development / Artificial Intelligence / Machine Learning - Employment Type: Full-time - Location: India - Work Mode: Listed under remote software development; confirm remote-work eligibility and location restrictions - Experience Required: 7–12 years of overall professional experience - Core Technologies: Python, LangChain, SQL, Generative AI, and LLMs - Cloud Platforms: AWS, Microsoft Azure, or Google Cloud Platform (GCP) - Salary: Not specified in the supplied listing Compensation, employment arrangements, and location eligibility should be confirmed with the hiring company or recruiter. 🏢 About the Role The Senior LLM Engineer will help design and implement advanced AI applications that can understand context, retrieve relevant information, and generate useful responses. The role combines hands-on software engineering with machine learning and Generative AI development. Candidates should be comfortable working across the AI development lifecycle, from solution design and architecture to implementation, deployment, testing, and optimization. 💼 Key Responsibilities Successful candidates may be expected to: - Design and develop Generative AI and LLM-based applications. - Build Retrieval-Augmented Generation (RAG) pipelines. - Use LangChain and other relevant frameworks to develop AI solutions. - Implement prompt engineering techniques to improve response quality. - Develop agent-based workflows for intelligent and context-aware applications. - Translate business requirements into scalable, production-ready AI systems. - Collaborate with engineering teams to shape technical roadmaps. - Work with business subject-matter experts and data teams to align AI solutions with practical requirements. - Participate in architecture discussions and code reviews. - Optimize AI application performance, reliability, and scalability. - Contribute to the deployment and maintenance of LLM-based solutions. 🎯 Required Qualifications and Skills Applicants should have the following skills and experience: - Python: Strong programming skills and practical software development experience. - LangChain: Experience building LLM-powered applications and workflows. - SQL: Ability to work with databases and retrieve or process data. - LLM Fundamentals: Understanding of how large language models work and how they can be applied to real-world problems. - Prompt Engineering: Knowledge of techniques for improving model responses and task performance. - Embeddings and Vector Databases: Understanding of semantic search and retrieval systems. - RAG Pipelines: Experience connecting language models to external knowledge sources. - Agent Workflows: Familiarity with frameworks and patterns for building AI agents. - Machine Learning: A background in machine learning or software engineering, with strong system-level thinking. - Cloud Computing: Experience with AWS, Azure, or GCP. - Communication: Ability to explain technical concepts and collaborate with stakeholders. - Independent Working: Ability to manage technical tasks while working effectively with cross-functional teams. The listing specifies 7–12 years of overall professional experience. ⭐ Preferred Qualifications The following experience may strengthen an application: - At least 1 year of hands-on experience with LLMs and Generative AI techniques. - Experience contributing to machine learning or AI product pipelines. - Experience deploying AI solutions from development through production. - Familiarity with MLOps practices. - Knowledge of scalable AI model deployment patterns. - Experience working with clients or cross-functional AI teams. - Experience optimizing LLM applications for performance and reliability. 🤖 Technologies and Concepts Candidates should be familiar with relevant technologies and concepts, including: - Python - LangChain - Large Language Models (LLMs) - Generative AI - Retrieval-Augmented Generation (RAG) - Prompt Engineering - Embeddings - Vector Databases - AI Agents - SQL - Machine Learning - MLOps - AWS, Azure, or GCP The exact technology stack may vary depending on the team's projects and requirements. 💰 Salary and Benefits The supplied job description does not mention a salary range or detailed benefits package. Before accepting an offer, candidates should confirm: - Salary and compensation structure. - Employment benefits and leave policies. - Whether the role is fully remote or requires office attendance. - Whether candidates living outside India are eligible. - The expected start date and interview process. 📝 How to Apply Interested candidates should review the original job listing and confirm the location and remote-work requirements before submitting an application. Apply Now