Apex Systems
Principal Gen AI Scientist
We are seeking a highly experienced Principal Gen AI Scientist with a strong focus on Generative AI (GenAI) to lead the design and development of cutting-edge AI Agents, Agentic Workflows, and GenAI Applications that solve complex business problems. This role requires advanced proficiency in Prompt Engineering, Large Language Models (LLMs), RAG, Graph RAG, MCP, A2A, multi-modal AI, GenAI Patterns, Evaluation Frameworks, Guardrails, data curation, and AWS cloud deployments. You will serve as a hands-on GenAI (data) scientist and critical thought leader, working alongside full stack developers, UX designers, product managers, and data engineers to shape and implement enterprise-grade GenAI solutions. Key Responsibilities Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications Develop, fine-tune, and optimize lightweight LLMs; evaluate models like Claude (Anthropic), Azure OpenAI, and open-source alternatives Design and deploy Retrieval-Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases Curate enterprise data using connectors integrated with AWS Bedrocks Knowledge Base/Elastic Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication Build and maintain Jupyter-based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS) Collaborate with cross-functional teams to build full-stack GenAI experiences Integrate GenAI solutions with enterprise platforms via API-based methods and standardized patterns Establish validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails Design and build robust ingestion pipelines for extracting, chunking, enriching, and anonymizing data from PDFs, video, and audio Orchestrate multimodal pipelines using scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows Implement embeddings to map media content to vector representations and integrate with vector stores (AWS KnowledgeBase/Elastic/Mongo Atlas) Required Qualifications PhD in AI/Data Science 10+ years of experience in AI/ML, with 3+ years in applied GenAI or LLM-based solutions Deep expertise in prompt engineering, fine-tuning, RAG, GraphRAG, vector databases, and multi-modal models Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow on EKS) Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.) Deep understanding of GenAI system patterns and architectural best practices Experience with Evaluation Frameworks and production-ready deployment standards Demonstrated ability to work in cross-functional agile teams GitHub Code Repository link required for each candidate Preferred Qualifications Published contributions or patents in AI/ML/LLM domains Hands-on experience with enterprise AI governance and ethical deployment frameworks Familiarity with CI/CD practices for ML Ops and scalable inference APIs EEO Employer Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.
We are seeking a highly experienced Principal Gen AI Scientist with a strong focus on Generative AI (GenAI) to lead the design and development of cutting-edge AI Agents, Agentic Workflows, and GenAI Applications that solve complex business problems. This role requires advanced proficiency in Prompt Engineering, Large Language Models (LLMs), RAG, Graph RAG, MCP, A2A, multi-modal AI, GenAI Patterns, Evaluation Frameworks, Guardrails, data curation, and AWS cloud deployments. You will serve as a hands-on GenAI (data) scientist and critical thought leader, working alongside full stack developers, UX designers, product managers, and data engineers to shape and implement enterprise-grade GenAI solutions. Key Responsibilities Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications Develop, fine-tune, and optimize lightweight LLMs; evaluate models like Claude (Anthropic), Azure OpenAI, and open-source alternatives Design and deploy Retrieval-Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases Curate enterprise data using connectors integrated with AWS Bedrocks Knowledge Base/Elastic Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication Build and maintain Jupyter-based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS) Collaborate with cross-functional teams to build full-stack GenAI experiences Integrate GenAI solutions with enterprise platforms via API-based methods and standardized patterns Establish validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails Design and build robust ingestion pipelines for extracting, chunking, enriching, and anonymizing data from PDFs, video, and audio Orchestrate multimodal pipelines using scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows Implement embeddings to map media content to vector representations and integrate with vector stores (AWS KnowledgeBase/Elastic/Mongo Atlas) Required Qualifications PhD in AI/Data Science 10+ years of experience in AI/ML, with 3+ years in applied GenAI or LLM-based solutions Deep expertise in prompt engineering, fine-tuning, RAG, GraphRAG, vector databases, and multi-modal models Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow on EKS) Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.) Deep understanding of GenAI system patterns and architectural best practices Experience with Evaluation Frameworks and production-ready deployment standards Demonstrated ability to work in cross-functional agile teams GitHub Code Repository link required for each candidate Preferred Qualifications Published contributions or patents in AI/ML/LLM domains Hands-on experience with enterprise AI governance and ethical deployment frameworks Familiarity with CI/CD practices for ML Ops and scalable inference APIs EEO Employer Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.