100% Onsite from day 1. Locals Only. If interested, please share resume to vivekk@acestackllc.com ---------------------------------------- Role: GenAI Developer Location: Boston, MA – 100% Onsite Long Term Contract – W2 / C2C Job Overview: We are seeking a Generative AI Developer with proven expertise in building, fine-tuning, and deploying LLM-based solutions for enterprise applications. The ideal candidate will have experience working with OpenAI, Hugging Face, or similar models, a strong understanding of prompt engineering, and familiarity with integrating GenAI into production pipelines. Key Responsibilities: • Design, develop, and deploy GenAI-based applications using LLMs (GPT, LLaMA, Claude, etc.) • Build and fine-tune models using open-source or proprietary frameworks • Create robust prompt engineering strategies, embeddings, and retrieval-augmented generation (RAG) workflows • Integrate GenAI capabilities into existing enterprise systems using APIs and microservices • Evaluate model performance and safety using custom metrics, guardrails, and monitoring tools • Collaborate with cross-functional teams (data engineers, product owners, MLOps) to gather requirements and implement solutions • Apply ethical AI practices, including bias detection and mitigation • Stay current with the latest advancements in generative AI and recommend relevant tooling or architecture upgrades Must-Have Skills: • 8-10+ Years of overall IT Experience. • 5+ years of experience in LLM/GenAI projects, as a GenAI Developer. • Strong knowledge of Python, Transformers, and deep learning frameworks (e.g., PyTorch, TensorFlow) • Experience with Hugging Face, OpenAI APIs, LangChain, or LLamaIndex • Knowledge of vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus) • Experience in prompt engineering, token optimization, and RAG pipelines • Familiarity with cloud platforms (preferably AWS, Azure, or GCP) and CI/CD for ML workflows Nice to Have: • Experience with streaming LLMs, chatbot frameworks, or voice-enabled GenAI apps • Knowledge of MLOps, Docker, Kubernetes, and MLflow • Understanding of data privacy, AI ethics, and compliance in GenAI applications • Domain exposure to healthcare, finance, or legal industries is a plus