{"schemaVersion":"jobsearcher.job.v1","id":"636fb1ea445a1c19f3630e41","url":"https://jobsearcher.com/jobs/636fb1ea445a1c19f3630e41","canonicalUrl":"https://jobsearcher.com/jobs/636fb1ea445a1c19f3630e41","title":"Data & AI Engineer","description":"While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.\n\nIf working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!\n\nAbout Quantiphi:\n\nQuantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations.\n\nSince our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake.\n\nHeadquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc.\n\nAs an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.\n\nOur industry recognition includes:\n\n21x Google Cloud Partner of the Year awards in the last 8 years.\n3x AWS AI/ML award wins.\n3x NVIDIA Partner of the Year titles.\n2x Snowflake Partner of the Year awards.\nTop analyst recognitions from Gartner, ISG, and Everest Group.\nConsecutive certifications as a Great Place to Work.\n\nBe part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.\n\nYour next big opportunity starts here!\n\nWork Location: USA - Remote\n\nExperience Level: 6+ years\n\nType: Contract (C2C)\n\nRole:\n\nWe are seeking an experienced Senior Data & AI Engineer to join our team in. In this role, you will be a key driver in building and modernizing our enterprise data and AI ecosystem. You will architect and deploy scalable real-time streaming pipelines, modern data products, semantic layers, knowledge graphs, and GenAI/Agentic data infrastructure. The ideal candidate blends deep expertise in large-scale data engineering with cutting-edge hands-on skills in AI engineering, RAG architectures, and automated data quality systems to power next-generation business capabilities.\n\nKey Responsibilities\n\nSenior Data and AI Engineering professional for large and complex data ecosystem leveraging data domains, data products, cloud and modern technology stack\nReal-Time Data Streaming: Design, build and maintain scalable and robust real-time data streaming pipelines using technologies such as Apache Kafka, AWS Kinesis, Spark streaming, or similar.\nSenior Data and AI Engineering professional responsible for Implementing Data and AI pipelines that bring together structured, semi-structured and unstructured data to support AI and Agentic solutions. This Includes pre-processing with extraction, chunking, embedding and grounding strategies to get the data ready.\nDesign and Develop Data and AI-driven systems to improve data capabilities, ensuring compliance with industry best practices.\nDesign and Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc.\nDesign and Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure.\nCollaborate with cross-functional teams to integrate solutions into operational processes and systems supporting various functions.\nStay up to date with industry advancements in GenAI and apply modern technologies and methodologies to our systems. This includes leading prototypes (POCs), conducting experiments, and recommending innovative tools and technologies to enhance data capabilities enabling business strategy.\nModel domain entities, relationships, and business logic in knowledge graphs (e.g., Neo4j, Amazon Neptune, RDF). Integrate data from multiple sources, ensuring canonical representation and semantic consistency.\nSynthetic data generation: Develop and validate synthetic data to simulate rare events and edge cases, supporting robust agent evaluation. Integrate synthetic data workflows with automated testing frameworks to ensure consistent, scalable agent performance assessment.\nIdentify and Champion AI driven Data Engineering productivity improvements capabilities accelerating end-to-end data delivery lifecycle. This includes researching and implementing innovative solutions such as AI-driven auto-generation of data pipelines, advanced DevOps practices (AI augmented self-healing data pipelines) for data and automated data quality frameworks.\nSemantic layer and Real time analytics: Design and implement scalable semantic layer with dynamic query translation to deliver real time insights for conversational analytics.\nIntegrate the semantic layers with AI/LLM platforms to provide low-latency, secure, and context-rich data access, optimized for high concurrency and aligned with enterprise governance standards.\nEnsure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management.\nImplement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies.\nCollaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems.\nMentoring junior team members and leading communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns.\nDesign and Develop graph database solutions for complex data relationships supporting AI systems, this also includes developing and optimizing queries (e.g., Cyhper, SPARQL) to enable complex reasoning, relationship discovery, and contextual enrichment for AI agents.\nDesign and Apply GenAI solutions to insurance-specific data use cases and challenges.\nPartner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment.\n\nSkills Required:\n\n6+ years of hands-on data engineering experience building large-scale, complex enterprise data ecosystems on cloud platforms (AWS, Azure, or GCP).\nDeep technical expertise in streaming platforms (Apache Kafka, AWS Kinesis, Spark Streaming) and distributed processing frameworks.\nProven track record in RAG architectures, vector search systems, chunking/embedding techniques, and data pipelines built specifically for LLM and Agentic AI consumption.\nExperience with graph databases (Neo4j, Amazon Neptune) and query languages (Cypher, SPARQL, or Gremlin).\nProficiency in domain-driven data design, dimensional modeling, semantic layer integration, and building reusable data products.\nHigh proficiency in Python, Scala, or Java, alongside SQL, DataOps, CI/CD, and containerized deployments.\nExperience in the Financial Industry handling complex, multi-structured domain data is strongly preferred.\nSoft Skills: Exceptional leadership, stakeholder communication, and cross-functional collaboration skills with a track record of mentoring team members.\n\nWhat is in it for you:\n\nBe part of the fastest-growing AI-first digital transformation and engineering company in the world\nBe a part of an energetic team of highly dynamic and talented individuals\nExposure to working with fortune 500 companies and innovative market disruptors\nExposure to the latest technologies related to artificial intelligence and machine learning, data and cloud\n\nIf you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!","company":"Quantiphi","rawCompany":"quantiphi","city":"Myrtle Point","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-09-28T11:51:26.094Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data & AI Engineer","description":"While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.\n\nIf working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!\n\nAbout Quantiphi:\n\nQuantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations.\n\nSince our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake.\n\nHeadquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc.\n\nAs an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.\n\nOur industry recognition includes:\n\n21x Google Cloud Partner of the Year awards in the last 8 years.\n3x AWS AI/ML award wins.\n3x NVIDIA Partner of the Year titles.\n2x Snowflake Partner of the Year awards.\nTop analyst recognitions from Gartner, ISG, and Everest Group.\nConsecutive certifications as a Great Place to Work.\n\nBe part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.\n\nYour next big opportunity starts here!\n\nWork Location: USA - Remote\n\nExperience Level: 6+ years\n\nType: Contract (C2C)\n\nRole:\n\nWe are seeking an experienced Senior Data & AI Engineer to join our team in. In this role, you will be a key driver in building and modernizing our enterprise data and AI ecosystem. You will architect and deploy scalable real-time streaming pipelines, modern data products, semantic layers, knowledge graphs, and GenAI/Agentic data infrastructure. The ideal candidate blends deep expertise in large-scale data engineering with cutting-edge hands-on skills in AI engineering, RAG architectures, and automated data quality systems to power next-generation business capabilities.\n\nKey Responsibilities\n\nSenior Data and AI Engineering professional for large and complex data ecosystem leveraging data domains, data products, cloud and modern technology stack\nReal-Time Data Streaming: Design, build and maintain scalable and robust real-time data streaming pipelines using technologies such as Apache Kafka, AWS Kinesis, Spark streaming, or similar.\nSenior Data and AI Engineering professional responsible for Implementing Data and AI pipelines that bring together structured, semi-structured and unstructured data to support AI and Agentic solutions. This Includes pre-processing with extraction, chunking, embedding and grounding strategies to get the data ready.\nDesign and Develop Data and AI-driven systems to improve data capabilities, ensuring compliance with industry best practices.\nDesign and Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc.\nDesign and Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure.\nCollaborate with cross-functional teams to integrate solutions into operational processes and systems supporting various functions.\nStay up to date with industry advancements in GenAI and apply modern technologies and methodologies to our systems. This includes leading prototypes (POCs), conducting experiments, and recommending innovative tools and technologies to enhance data capabilities enabling business strategy.\nModel domain entities, relationships, and business logic in knowledge graphs (e.g., Neo4j, Amazon Neptune, RDF). Integrate data from multiple sources, ensuring canonical representation and semantic consistency.\nSynthetic data generation: Develop and validate synthetic data to simulate rare events and edge cases, supporting robust agent evaluation. Integrate synthetic data workflows with automated testing frameworks to ensure consistent, scalable agent performance assessment.\nIdentify and Champion AI driven Data Engineering productivity improvements capabilities accelerating end-to-end data delivery lifecycle. This includes researching and implementing innovative solutions such as AI-driven auto-generation of data pipelines, advanced DevOps practices (AI augmented self-healing data pipelines) for data and automated data quality frameworks.\nSemantic layer and Real time analytics: Design and implement scalable semantic layer with dynamic query translation to deliver real time insights for conversational analytics.\nIntegrate the semantic layers with AI/LLM platforms to provide low-latency, secure, and context-rich data access, optimized for high concurrency and aligned with enterprise governance standards.\nEnsure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management.\nImplement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies.\nCollaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems.\nMentoring junior team members and leading communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns.\nDesign and Develop graph database solutions for complex data relationships supporting AI systems, this also includes developing and optimizing queries (e.g., Cyhper, SPARQL) to enable complex reasoning, relationship discovery, and contextual enrichment for AI agents.\nDesign and Apply GenAI solutions to insurance-specific data use cases and challenges.\nPartner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment.\n\nSkills Required:\n\n6+ years of hands-on data engineering experience building large-scale, complex enterprise data ecosystems on cloud platforms (AWS, Azure, or GCP).\nDeep technical expertise in streaming platforms (Apache Kafka, AWS Kinesis, Spark Streaming) and distributed processing frameworks.\nProven track record in RAG architectures, vector search systems, chunking/embedding techniques, and data pipelines built specifically for LLM and Agentic AI consumption.\nExperience with graph databases (Neo4j, Amazon Neptune) and query languages (Cypher, SPARQL, or Gremlin).\nProficiency in domain-driven data design, dimensional modeling, semantic layer integration, and building reusable data products.\nHigh proficiency in Python, Scala, or Java, alongside SQL, DataOps, CI/CD, and containerized deployments.\nExperience in the Financial Industry handling complex, multi-structured domain data is strongly preferred.\nSoft Skills: Exceptional leadership, stakeholder communication, and cross-functional collaboration skills with a track record of mentoring team members.\n\nWhat is in it for you:\n\nBe part of the fastest-growing AI-first digital transformation and engineering company in the world\nBe a part of an energetic team of highly dynamic and talented individuals\nExposure to working with fortune 500 companies and innovative market disruptors\nExposure to the latest technologies related to artificial intelligence and machine learning, data and cloud\n\nIf you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!","datePosted":"2026-09-28T11:51:26.094Z","dateModified":"2026-09-28T11:51:26.094Z","hiringOrganization":{"@type":"Organization","name":"Quantiphi","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Myrtle Point","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"636fb1ea445a1c19f3630e41"},"url":"https://jobsearcher.com/jobs/636fb1ea445a1c19f3630e41"}}