12 jobs found

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Job Description Shape the Future of Enterprise AI at Scale We are looking for a seasoned Software Architect (Sr. Consultant title at Visa) to join our Corporate Generative AI Technologies team. In this role, you will help architect, build, and scale enterprise-grade Generative AI and agentic applications. This is a senior, hands-on engineering role for someone who brings strong system design judgment, full-stack product engineering depth, and the ability to translate complex business workflows into scalable, reliable AI-enabled automation solutions. You will work on platforms and applications that use AI-native application patterns, including large language models, agentic workflows, retrieval-augmented generation, tool orchestration, API integrations, ETL pipelines, and data systems to transform business processes into intelligent, reliable, and scalable workflows. You will help solve hard engineering problems such as decomposing complex workflows into reusable agents, designing secure human-in-the-loop systems, and building production-grade GenAI applications that can be monitored, evaluated, governed, and continuously improved. As a Senior Consultant (Staff Software Architect), you will operate with a high degree of autonomy, ownership, and technical judgment while collaborating closely with your manager and the broader engineering team to align on technical direction. You will be responsible for building high-quality software while also influencing system design decisions, architectural direction, engineering standards, and best practices across the team. Key Responsibilities Design, build, and scale enterprise-grade GenAI and agentic applications, with a strong focus on maintainable, secure, scalable, reliable, and production-ready architecture. Own architecture and delivery of major GenAI subsystems; lead design reviews; mentor I4/I5 engineers; define reusable patterns and production standards. Apply strong system design judgment to build full-stack, production-grade applications with robust API design, workflow orchestration, secure data flows, observability, and operational readiness. Build modern frontend experiences using React and established frontend patterns, including component-based architecture, state management, reusable UI components, accessibility, performance optimization, and seamless integration with backend APIs and AI-enabled services. Design and implement scalable backend services using Python, Node.js, and/or Java, including secure APIs, asynchronous processing, background jobs, authentication, authorization, logging, error handling, and system resiliency. Work with databases like PostgreSQL, Redis, vector databases, and related technologies, including schema design, indexing strategies, query optimization, transaction management, caching patterns, migrations, and data access patterns. Implement backend capabilities for AI-enabled and agentic workflow automation, including intent routing, agent orchestration, tool execution, API integrations, data retrieval, multi-step execution, workflow state management, human approval flows, guardrails, auditability, and enterprise system integration. Develop AI-native capabilities using OpenAI, Anthropic, and related LLM APIs/SDKs, including prompt orchestration, tool/function calling, structured outputs, streaming responses, model routing, and evaluation patterns. Apply deep knowledge of modern LLM capabilities to make informed engineering decisions around model selection, context management, latency, cost, reliability, output quality, safety, and user experience. Design and implement retrieval-augmented generation solutions, including ingestion pipelines, ETL workflows, embeddings, vector database integration, retrieval strategies, relevance ranking, grounding, and retrieval quality evaluation. Build and deploy cloud-native applications using containers, DevOps practices, CI/CD pipelines, automated testing, monitoring, and operational automation. Work closely with engineering teammates and cross-functional partners to align with team priorities, translate ambiguous requirements into proof-of-concepts, then evolve them into production-quality solutions through shared ownership and hands-on collaboration. Implement observability and operational excellence for GenAI applications, including end-to-end tracing, workflow telemetry, model evaluation, and monitoring to ensure secure, reliable, and production-ready AI systems. Technical Skills: Languages & Frameworks: Python, FastAPI, LangGraph Cloud & Infrastructure: AWS, Azure, Docker, Kubernetes, ECS DevOps: Git, CI/CD pipelines Anthropic / OpenAI SDKs, MCP, A2A Databases & Storage: Pinecone, Redis, PostgreSQL Monitoring & Governance: Prometheus, Grafana, audit logging, access control Frontend: ReactJS, HTML, CSS, JavaScript Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 8+ years of relevant work experience with a Bachelor's Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience. At least 8 years of experience designing, building, and operating complex distributed software systems in production environments. Strong background in software architecture, distributed systems, API design, cloud-native platforms, and data-intensive applications. Experience with cloud platforms, containerized environments, CI/CD systems, and observability tooling. Hands-on experience with React and backend development using Python, Node.js, Java, or similar languages. Strong communication skills with the ability to translate complex technical concepts to business stakeholders Preferred Qualifications: 9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD Experience building AI-enabled, data-driven, workflow automation, search, conversational, or machine learning-powered applications is highly valued. Direct experience with Generative AI technologies, LLMs, RAG architectures, or agentic systems is preferred but not required for candidates with exceptional software architecture and distributed systems experience. Experience driving technical strategy and influencing architectural direction across organizations. Expertise in system design tradeoffs involving scalability, security, reliability, performance, cost, and developer productivity. Deep understanding of modern LLM ecosystems, agent frameworks, retrieval architectures, and enterprise AI deployment patterns. Familiarity with modern AI architectures including agentic workflows, memory systems, tool orchestration, MCP, and A2A frameworks Proven ability to lead cross-functional AI initiatives, including PoC development, stakeholder alignment, and enterprise rollout. Information for US Applicants For roles located in the US, the estimated salary range for this position is $162,500.00 to $ 260,400.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.

About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Visa will accept applications for this role until at least 09-30-2026 Job Description We are seeking a highly skilled AI developer with deep expertise in Agentic and Generative AI to drive the next wave of intelligent automation and digital transformation. In this role, you will be at the forefront of designing, implementing, and optimizing AI-powered solutions integrated into the ServiceNow platform. Your primary focus will be on leveraging artificial intelligence, including custom MCP tooling, Agentic scoped applications, and third-party Large Language Models-to enhance workflows, automate complex processes, and deliver innovative business outcomes. You will architect and build custom AI solutions and ensure seamless user experiences through intelligent automation. As a thought leader in AI, you will collaborate with stakeholders to identify opportunities for AI adoption, experiment with emerging technologies, and contribute to Visa's enterprise AI strategy. In addition to your AI responsibilities, you will develop and configure integrations between ServiceNow and other enterprise applications, manage the full lifecycle of these integrations (from API development and scripting to framework deployment), and ensure robust, secure, and scalable connections. Roles and responsibilities: Designing, developing, and optimizing AI-powered solutions (built within the ServiceNow platform and/or integrated through external custom solutions), including the creation of custom MCP tooling and Agentic solutions. Leveraging AI solutions to integrate and orchestrate third-party Large Language Models (LLMs) such as OpenAI, Google Gemini, etc, driving intelligent automation and enhanced user experiences. Collaborating with stakeholders to identify opportunities for AI adoption, experiment with emerging technologies, and deliver innovative, AI-driven business outcomes. Troubleshooting and resolving issues with ServiceNow configurations and AI components, ensuring seamless operation and reliability. Identifying requirement gaps to ensure high-quality solutions and providing configuration options with clear pros and cons. Designing and implementing intuitive, user-friendly software that enables customer-led customization and flexibility. Collaborating with internal customers and business analysts to clarify requirements and architect effective, AI-driven solutions. Authoring comprehensive technical design and build documentation for all facets of the technical infrastructure. Conducting research and analysis of existing systems to provide accurate time estimates and recommendations to project managers. Actively participating in project meetings and daily scrums to communicate development status, progress, and technical insights. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Visa will accept applications for this role until at least September 30, 2026. Qualifications Basic Qualifications 5+ years of relevant work experience with a Bachelor's Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience. Preferred Qualifications Proven ability to deliver projects on time and within budget by writing high-quality code, mentoring junior developers, understanding workload and usage requirements, and producing clear technical documentation that enables knowledge transfer and long-term supportability across global teams. Experience designing robust, scalable, and moderately complex architectural solutions that integrate across a broader technical ecosystem, while effectively operating as a collaborative member of a globally distributed team across diverse time zones and cultures. Minimum of 2 years of relevant professional experience including hands-on work with AI-powered solutions, with a bachelor's degree; or at least 2 years of relevant experience with an Advanced Degree (e.g., Master's, MBA, JD, MD). In-depth knowledge of APIs, web services, and standard relational database concepts. Proven experience with JavaScript, AJAX, JSON, CSS, REST, SOAP, and HTML. Strong Python skills and hands-on experience building RESTful or GraphQL APIs. Demonstrated experience building GenAI solutions, agents, or conversational applications, exhibiting the ability to differentiate reasoning approaches like ReAct and Chain-of-Thought (CoT). Demonstrate ability to design and architect Agentic Systems, applying various agent architectures (symbolic, BDI, LLM-based) to design intelligent agents tailored for specific tasks and environments. Implement Core Agent Capabilities. Develop agents that can perceive, reason, plan, act, and learn, utilizing Python and relevant AI libraries and frameworks. Analyze and Evaluate Agent Behavior. Critically assess agent performance, understand the complexities of multi-agent systems and human-agent interaction, and identify risks. Navigate Ethical Landscapes. Identify, analyze, and address the ethical challenges and safety considerations inherent in developing and deploying autonomous AI systems, applying principles of responsible AI. Apply Agentic AI to Solve Problems. Conceptualize and build functional AI agents for practical applications, demonstrating the ability to integrate diverse concepts into cohesive business solutions. Deep understanding of prompt engineering concepts, LLM fine-tuning, and retrieval-augmented generation (RAG). Familiarity with MCP servers or comparable model-serving/hosting platforms. Excellent problem-solving skills, strong communication, and a collaborative attitude. Strong analytical skills with the ability to extensively analyze and improve business processes and workflows. Demonstrated expertise in designing, implementing, and optimizing AI-driven functionalities integrated with ServiceNow, such as custom Agentic AI skills, GenAI integrations, and intelligent automation. Strong technical background in ServiceNow-specific development tools and frameworks (UI Policies, UI Macros, UI Pages, Client Scripts, Script Includes, Business Rules, Mid Server Configuration & Architecture, Import Sets, Transform Maps, Update Sets). Strong knowledge of the CMDB, data modeling, data strategies, and integrations. Knowledge of ServiceNow ITSM/ITOM product portfolio including Change Management, Discovery, and Service Mapping. Relevant certifications such as Certified ServiceNow Admin (CSA), Certified Implementation Specialist (CIS), or Certified Application Developer (CAD) are highly desirable. Information for US Applicants For roles located in the US, the estimated salary range for this position is $124,300.00 to $ 198,600.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.