GenAI Architect-2

Job Type: Contract Job Category: IT Job Title: GenAI Architect Location: North Quincy, MA (Onsite) Duration: 6 Months Employment Type: Contract Job Summary We are seeking an experienced GenAI Architect to lead the design, development, and deployment of enterprise-grade Generative AI solutions. The ideal candidate will have deep expertise in modern AI/ML frameworks, foundation models, LLM architectures, vector databases, and cloud-native ecosystems. This role involves close collaboration with data scientists, engineers, business stakeholders, and security teams to architect scalable and compliant AI systems tailored to business needs. Key Responsibilities Architect end-to-end Generative AI solutions, including model selection, fine-tuning, prompt engineering, retrieval-augmented generation (RAG), and deployment strategies. Develop scalable AI application architectures leveraging cloud platforms (AWS/Azure/GCP), containerization, orchestration, and MLOps pipelines. Evaluate, customize, and integrate foundation models (LLMs, Vision Models, Multimodal Models) into enterprise workflows. Lead the design of vector search, embeddings, and knowledge-retrieval systems for enterprise data. Partner with security and compliance teams to ensure AI systems meet data governance, risk, and regulatory requirements. Provide hands-on technical mentorship to engineering and data teams implementing AI features and pipelines. Define best practices for model monitoring, drift detection, data quality management, and model lifecycle management. Collaborate with product and business teams to translate use-case requirements into robust AI solution architectures. Conduct POCs, feasibility studies, and performance benchmarking for new AI technologies and models. Required Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field. 8+ years of experience in software or data engineering, including at least 3+ years focused on AI/ML and hands-on experience in GenAI/LLMs. Deep knowledge of LLM frameworks (HuggingFace, LangChain, LlamaIndex, TensorFlow, PyTorch). Proven experience with RAG systems, embeddings, vector databases (Pinecone, FAISS, Weaviate, Milvus). Strong understanding of cloud services (AWS Sagemaker, Azure OpenAI, Google Vertex AI) and MLOps tools (MLflow, Kubeflow). Experience fine-tuning LLMs and working with prompt engineering techniques. Expertise in Python and familiarity with API development, microservices, and serverless architectures. Knowledge of data privacy, compliance, and responsible AI principles. Preferred Qualifications Experience implementing multimodal AI (text, vision, audio). Background in financial services or regulated enterprise environments. Familiarity with vector indexing optimization, distributed model inference, or model compression techniques. Prior experience leading technical architecture for large-scale AI deployments. Required Skills PERFORMANCE ARCHITECT