Job description

Job Title: Product Architect and AI Lead Location :- Sleepy Hollow, NY Hybrid Position : 3 Days WFO - 2 days Remote Employment Type: Full-Time Role Overview: We are seeking an experienced Product Architect and AI Lead to spearhead the design, development, and implementation of cutting-edge AI-driven solutions. This pivotal role requires deep expertise in AI/ML, Retrieval-Augmented Generation (RAG), GraphRAG, Vector Databases (VectorDBs), agentic AI, and enterprise-scale systems. The ideal candidate will possess strong technical leadership, strategic thinking, and hands-on experience in AI architecture using cloud-native environments. Key Responsibilities: AI Product Design and Architecture: Lead the conceptualization, architecture, and implementation of scalable AI-driven products and solutions. Utilize Retrieval-Augmented Generation (RAG) and GraphRAG frameworks to enhance the accuracy and context-awareness of AI models. Integrate structured and unstructured data into cohesive AI systems, leveraging VectorDBs and knowledge graphs. Enterprise Data Management: Ensure robust data preparation processes, including data cleaning, normalization, enrichment, and embedding generation. Manage the seamless integration and harmonization of structured databases (SQL) and unstructured data sources (text, documents). Agentic AI & Multi-Agent Systems: Design and implement autonomous, decision-making AI agents with modular architectures including perception layers, reasoning engines, memory systems, and action layers. Utilize frameworks such as LangChain, CrewAI, and LangGraph to build collaborative multi-agent environments. Performance Optimization & Scalability: Optimize GenAI pipelines for low latency, ensuring real-time responsiveness in enterprise applications. Employ advanced techniques like model quantization, distillation, caching strategies, and efficient indexing. Privacy and Security Compliance: Enforce strict enterprise data privacy through differential privacy, federated learning, encryption, and on-premise or secure cloud deployments. Ensure compliance with GDPR, HIPAA, and other relevant privacy regulations. Explainable AI (XAI): Implement transparency measures including attention visualization, SHAP, LIME, and chain-of-thought prompting to facilitate user trust and regulatory compliance. Evaluation and Quality Assurance: Develop comprehensive evaluation metrics to assess retrieval accuracy (precision@K, recall), generation quality (ROUGE, BLEU), and overall AI system performance. Conduct human-in-the-loop validations and employ A/B testing to measure effectiveness and improvements. Collaboration and Team Leadership: Lead cross-functional teams, ensuring clear communication and coordination among data scientists, engineers, and stakeholders. Mentor and guide team members, fostering an environment of continuous learning and innovation. Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or related fields. Extensive experience in AI/ML development, including hands-on implementation of Retrieval-Augmented Generation (RAG), GraphRAG, and agentic AI frameworks. Strong proficiency with cloud platforms (AWS, Azure, GCP), specifically AWS services like SageMaker, Bedrock, Lambda, API Gateway, DynamoDB, EC2, and RDS. Expertise in Vector Databases (Pinecone, FAISS), graph databases (Neo4j), and structured/unstructured data integration. Demonstrated experience building scalable, high-performance GenAI pipelines with attention to data privacy and compliance. Proven ability to deliver explainable and transparent AI solutions. Exceptional communication, leadership, and strategic planning skills. Preferred Skills: Familiarity with frameworks such as LangChain, CrewAI, and LangGraph. Experience with Apache Spark, Kafka, and distributed systems. Background in fine-tuning and deploying custom Small Language Models (SLMs) or Large Language Models (LLMs) on enterprise data. Knowledge of privacy-preserving techniques including differential privacy and federated learning.

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