GenAI Engineer (0 to 3yrs)

GenAI Engineer role for early-career engineers building production-ready Generative AI applications. The team works on LLMs, RAG, AI agents, and modern AI development frameworks across multiple domains. Role: GenAI Engineer (0 to 3yrs) Location: Pune Experience:0 to 3 years of experience in software development, AI/ML, data science, or GenAI application developmentStrong programming skills in PythonAbility to write clean code, debug issues, and learn new technologies quicklyGood problem-solving skills and willingness to work on real-world business problemsStrong communication skills and ability to work in a team environmentResponsibilities:Build GenAI applications using large language modelsDevelop retrieval-augmented generation applicationsWork on AI agents and agentic workflowsCreate APIs and backend servicesIntegrate LLMs with databases, documents, APIs, business tools, and external systemsWrite clean, maintainable, and well-documented code for AI applicationsExperiment with prompts, tools, memory, function calling, structured outputs, and evaluation techniquesSupport testing, debugging, and performance improvement of GenAI applicationsCollaborate with senior engineers to convert business requirements into working AI solutionsAssist in deployment, monitoring, and optimization of AI-powered applicationsStay updated with developments in GenAI, LLMs, AI agents, RAG, and applied AI engineeringAdditional responsibilities:Work closely with senior engineers, product teams, and clientsDesign, develop, test, and deploy GenAI solutions across healthcare, education, enterprise automation, finance, and customer supportWork with vector databases and related platformsUse modern AI development frameworks and related librariesHybrid flexibilityLearning-first culture via TMLC AcademyCompetitive compensation aligned with impactWork alongside Kaggle Grandmasters and top AI researchers on frontier problemsReal ownership and surface area with outcomes, not ticketsNice to have:Hands-on experience or project exposure to LangChain, LangGraph, CrewAI, LlamaIndex, or similar frameworksExposure to vector databases such as Chroma, FAISS, Qdrant, Pinecone, or WeaviateBasic understanding of Large Language Models, prompt engineering, embeddings, and vector searchGood understanding of APIs, JSON, REST, and backend developmentFamiliarity with FastAPI, Flask, or similar Python web frameworksBasic knowledge of databases such as PostgreSQL, MongoDB, or MySQLUnderstanding of RAG pipelines, document processing, chunking, retrieval, and response generationAI agentsfunction callingMCPfine-tuningLoRAevaluation tools like RAGAS or LangSmithDockercloud platformsopen-source LLM deploymentMore skills:open-source LLMs, vector databases, document loaders, retrieval pipelines, AI agents, agentic workflows, APIs, backend development, JSON, REST, PostgreSQL, MongoDB, MySQL, Chroma, FAISS, Qdrant, Pinecone, Weaviate, chunking, response generation .