LLM Full Stack Engineer

THE WORK: Explore the fascinating world of Large Language Models and immerse yourself in a role where your independent contributions will shape innovative solutions. You will actively participate in discussions and collaborate to provide thoughtful answers to complex challenges. This opportunity invites you to grow as a subject matter expert while engaging with cutting-edge technology. Join us in this exciting journey and make a meaningful impact.Responsibilities:Design and develop AI/ML and Generative AI solutions using PythonBuild and deploy applications leveraging Large Language Models (LLMs)Develop end-to-end pipelines including data ingestion, preprocessing, model integration, and deploymentImplement prompt engineering and fine-tuning strategies for LLMsIntegrate AI services into web/mobile/backend applications via APIsWork with vector databases and embeddings for semantic search and RAG architecturesOptimize models and pipelines for performance, latency, and costCollaborate with cross-functional teams to translate business requirements into AI solutionsEnsure responsible AI practices including data privacy, bias mitigation, and explainabilityMonitor and improve model performance in production environments________________________________________Required Skills Qualifications6-8 years of experience in software engineering / AI / ML, Python roles, Strong programming expertise in PythonHands-on experience with ML/DL frameworks like PyTorch or TensorFlowExperience with LLM frameworks such as LangChain or LlamaIndexSolid understanding of NLP concepts and transformer-based modelsExperience with REST APIs and microservices architectureFamiliarity with vector databases (e.g., Pinecone, FAISS, Weaviate)Experience with version control systems like Git________________________________________Preferred QualificationsExperience working with APIs from providers like OpenAI or open-source LLMs (Llama, Mistral)Knowledge of Retrieval-Augmented Generation (RAG) architecturesExperience with model fine-tuning and evaluation techniquesExposure to cloud platforms (AWS / GCP) for deployment (excluding Azure)Understanding of containerization tools like Docker________________________________________Soft SkillsStrong analytical and problem-solving skillsAbility to translate complex AI concepts into practical solutionsGood communication and stakeholder management skillsAbility to work independently and in collaborative environments________________________________________Nice to HaveExperience with AI agents / autonomous workflowsKnowledge of MLOps practices and CI/CD for ML pipelinesExposure to multimodal AI (text, image, audio models)Experience with real-time AI applications (chatbots, voice bots, copilots)


Qualification