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Senior/Staff LLM & GenAI Engineer (Python | LangChain | RAG)

🏢 First Phoenics Solutions  •  📍 India

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Job Description

Job Title – Sr./Staff GenAI Engineer Location – Mumbai (Goregaon)- 3 days reports to Office Experience – 9+ years Employment Type – Fulltime Notice Period – Immediate Joiners Preferred Mandatory – • Strong expertise in LLMs, prompt engineering, RAG, and AI agents. • 9-12 years building production-grade ML systems. • Advanced Python skills with LangChain/LangGraph experience. • Proficient in SQL for data manipulation and building pipelines. • Hands-on experience deploying GenAI apps on Azure/GCP/AWS. • Ability to design scalable, high-performance GenAI architectures. • Excellent communication for cross-functional collaboration. • Proven ability to mentor, lead, and drive innovation in GenAI Required skills • 8+ years of professional experience in building Machine Learning models & systems for Sr GenAI Engineer and 10+ years for Staff GenAI Engineer • 1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents. • Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must. • Understanding of Cloud services from various cloud services from Azure, GCP, or AWS for building the GenAI applications • Excellent communication skills to effectively collaborate with business SMEs Roles & Responsibilities • Develop and optimize LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures. • Codebase ownership: Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices. • Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes. • Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products. • Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development. • Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.
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