7 Enterprise Ai Jobs

You will be joining TheMathCompany, a global Enterprise AI and Analytics company known for its data-driven decision-making solutions for leading Fortune 500 and Global 2000 enterprises. Established in 2016, MathCo specializes in developing custom AI and advanced analytics solutions to address enterprise challenges through its unique hybrid model. Our proprietary platform, NucliOS, features pre-built workflows and reusable plug-and-play modules, facilitating connected intelligence with reduced total cost of ownership. At MathCo, we cultivate an open, transparent, and collaborative work culture devoid of barriers, creating an excellent work environment for our employees. We offer stimulating opportunities for professional growth, prioritize capabilities and attitude over experience, empowering our team members, or Mathemagicians, to make a lasting impact.,

You should have a Bachelor's degree in Computer Science, Engineering, Business, or a related technical field, or equivalent practical experience. Your experience should include 15 years in technology, product management, consulting, or a related field, with a focus on AI/ML solutions. Additionally, you should have 7 years of experience in a senior leadership role managing teams (20+ individuals), focusing on AI strategy, solution development, or product delivery. It is important to have experience in senior stakeholder engagement, including working with executive-level decision-makers. Moreover, you should have experience in defining and executing an AI strategy, and developing prototypes into products. It would be preferable if you possess a Master's degree or PhD in a relevant technical field (e.g., AI, Machine Learning, Data Science). You should also have experience with Agentic AI principles and applications, particularly in an enterprise context. A strong penchant for and existing knowledge of the advances in AI, especially Enterprise AI, is desired. Deep understanding of HR operations, processes, and product areas is also essential. Furthermore, you should have the ability to manage complex organizational change and overcome barriers to adoption for new technology solutions. An imagination and vision for how these advances can impact an HR function, HR personas, and HR critical journeys that drive stellar experience, aim for efficiency, and enable effectiveness for Googlers would be beneficial. The Google People Services, Operations function is the services and program management group within People Operations that makes HR stuff easy and intuitive for Googlers. The global team optimizes people processes, from problem definition to execution, partnering with teams across People Operations and engineering to innovate and technology in the way they attract, retain, and grow Googlers worldwide. The focus is on providing an amazing experience to past, present, and future Googlers, delivering operational services, managing the contingent workforce, and implementing HR programs across various countries. Members of the Operations team have the opportunity to create, develop, and implement complex global operations regardless of location or level of experience. As the Director of AI Garage for People Operations at Google, you will be a pivotal senior leader responsible for shaping and executing the future of AI-driven innovation within the People Ops landscape. This role is highly impactful and pioneering for business transformation using AI. You will lead a talented team focused on identifying transformative use cases within People Operations with an emphasis on Agentic AI. Leading the successful setup of the first ever dedicated in-house AI Garage, you will be responsible for rapid envisioning, prototyping, iterating, launching, landing, and ongoing maintenance of AI solutions for various POps personas and Critical User Journeys (CUJs). You will serve as the key interface between strategic vision and operational execution, closely partnering with HR Engineering teams. Responsibilities include defining, articulating, and evolving a compelling AI strategy for People Operations aligned with broader Google and POps organizational goals, developing and advocating thought leadership on how AI can transform an HR function, partnering with engineers and product managers to develop prototypes and production-ready solutions, building and maintaining strong relationships with senior leaders and teams across People Operations, process owners, Centers of Excellence, and especially HR Engineering, and developing and executing comprehensive change management strategies, establishing a robust framework for documenting insights, challenges, and successes.,

4+ years of experience as a Data Scientist. Hands-on experience with Azure AI services and tools. Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), data insights, reasoning agents, and chain of thought reasoning. Knowledge of Graph Databases such as Cosmos DB, Neo4j, and other graph data management systems. Expertise in prompt engineering to optimize AI model interactions. Experience in API development and integration. Domain expertise in Finance and Data Management. Proven track record working on enterprise AI use cases, including at least one successful go-live solution.

Overview: We are seeking an exceptional and technically accomplished Senior Data Scientist to join our rapidly growing team. This role is ideal for a hands-on AI expert with deep experience in Large Language Models (LLMs) , Natural Language Processing (NLP) , Cognitive AI , Conversational AI , and Agentic AI systems . You will work on designing, developing, and scaling state-of-the-art AI solutions that drive business innovation, operational intelligence, and customer experience transformation. This is a high-impact individual contributor role, focused on technical excellence and product-grade AI development. Key Responsibilities LLM & Cognitive AI Solution Development Architect and fine-tune LLM-based solutions (e.g., GPT, LLaMA, Claude, Mistral) using transfer learning, PEFT, and retrieval-augmented generation (RAG). Develop Agentic AI architectures with autonomous behavior and multi-agent collaboration capabilities. Apply prompt engineering , in-context learning , and tool former-style techniques to enable complex reasoning and task execution. Build Conversational AI systems using Transformer-based backbones and orchestration tools (LangChain, Haystack, Rasa, Semantic Kernel). Natural Language Processing (NLP) Design and implement advanced NLP pipelines for semantic search, summarization, NER, text classification, and knowledge extraction. Utilize and integrate tools such as SpaCy , BERT , RoBERTa , GloVe , Word2Vec , NLTK , and TextBlob . Conduct advanced text preprocessing, dependency parsing, sentiment analysis, tokenization, and multilingual NLP modeling. AI/ML Engineering Build scalable ML pipelines with FastAPI, gRPC, and RESTful interfaces. Containerize services using Docker and deploy to production environments via Kubernetes and cloud-native workflows. Integrate models into real-time and batch data systems, optimizing for latency, throughput, and reliability. Cloud & Infrastructure Develop and deploy solutions on AWS , Azure , or Google Cloud Platform (GCP) . Leverage services like SageMaker, Vertex AI, Azure ML Studio, and serverless orchestration tools. MLOps & CI/CD Design and maintain end-to-end MLOps pipelines using tools like MLflow, Kubeflow, or TFX for reproducibility and traceability. Automate model testing, monitoring, versioning, and rollback strategies in production. Big Data & Analytics Apply Spark, Hadoop, and Hive to process large-scale datasets efficiently. Perform complex data transformations and statistical modeling to extract actionable insights. Database & Data Engineering Interface with SQL and NoSQL systems (PostgreSQL, MongoDB, DynamoDB, etc.) for efficient data retrieval and processing. Design data schemas and optimize query performance for AI-centric applications. Cross-functional Collaboration Work closely with product managers, engineers, and domain experts to identify high-impact problems and deliver AI-driven solutions. Communicate findings and solution architectures clearly to technical and non-technical stakeholders. Technical Skills Expert in Python , PyTorch, HuggingFace Transformers, LangChain, and OpenAI/Anthropic/LLama APIs. Deep understanding of Transformer architectures , Attention Mechanisms , and LLM fine-tuning techniques . Familiarity with Agentic AI paradigms , including memory management, autonomous goal completion, and tool use. Strong experience with cloud platforms, container orchestration (Docker + Kubernetes), and deployment automation. Proficient in statistical modeling, probabilistic reasoning, and experimental design. Bonus Experience in Online Reputation Management (ORM) or product-centric platforms . Publications or open-source contributions in AI/ML/NLP.

Role Overview: We' re looking for a Lead Data Scientist to join our fast-growing, mission-driven team. This is a high-impact leadership role at the intersection of technology, strategy, and innovation where your expertise will power intelligent solutions that redefine how we think about data, products, and customer experience. If you thrive in high-performance environments and want to lead cutting-edge projects with Generative AI, LLMs, and large-scale NLP systems, this is your opportunity to make a lasting impact. Key Responsibilities: Build the Future with AI/ML Architect scalable AI systems to solve real-world, high-value business challenges cross domains. Design and deploy cutting-edge solutions with Generative AI, Transformer architectures, and custom Large Language Models (LLMs). Apply state-of-the-art ML techniques prompt engineering, transfer learning, multi-modal learning to push the boundaries of what's possible. NLP at Scale Lead the development of advanced NLP systems: semantic search, question answering, summarization, classification, and conversational AI. Work with best-in-class models and libraries: BERT, GPT, RoBERTa, Word2Vec, SpaCy, NLTK, Hugging Face Transformers, and more. Leverage language understanding to transform unstructured data into strategic insights. Full-Lifecycle Model Deployment Build robust MLOps pipelines for training, testing, deployment, and monitoring using MLflow, Kubeflow, Airflow, and CI/CD tools. Containerize and orchestrate AI models using Docker and Kubernetes across cloud environments (AWS, GCP, Azure). Design APIs and inference services using FastAPI or gRPC, optimized for performance, scalability, and uptime. Lead, Inspire, and Elevate Build and mentor a world-class data science team, nurturing talent and fostering a culture of curiosity, experimentation, and technical excellence. Drive the data science strategy, influence key decisions, and align AI initiatives with business goals. Establish best-in-class practices for model development, code quality, documentation, and performance evaluation. Data at the Core Work hands-on with structured, semi-structured, and unstructured data. Optimize high-volume data pipelines, integrate with SQL and NoSQL databases, and leverage big data ecosystems like Spark, Hive, and Hadoop. Use statistical modeling and experimental design to derive actionable intelligence from data Collaborate Across the Enterprise Work closely with engineering, product, and executive teams to define problems, explore solutions, and deliver AI products that move the needle. Translate technical concepts into strategic recommendations and insights that influence roadmaps and revenue. Champion AI literacy and advocate for ethical, explainable, and scalable data science across the organization. Education Bachelors or Master’s in Computer Science, AI, Data Science, Machine Learning, Engineering, or a related technical discipline. PhD is a plus. Experience 6+ years of experience in data science or machine learning, with 2+ years in a leadership or managerial role. Proven record of building and deploying AI solutions at scale in real-world production environments. Experience in GenAI, NLP, cloud-native architectures, and full-cycle ML development. Technical Expertise Languages & Libraries: Python, Scikit-learn, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas NLP: BERT, GPT, Word2Vec, SpaCy, NLTK, TextBlob, CoreNLP, Transformer-based architectures Cloud & Deployment: AWS, Azure, GCP, Docker, Kubernetes, FastAPI, gRPC Big Data: Spark, Hive, Hadoop, Kafka Data Systems: PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery MLOps & Monitoring: MLflow, Airflow, Kubeflow, Prometheus, Grafana Nice to Have Experience in online reputation management, customer analytics, or product-led organizations. Familiarity with responsible AI, fairness, and explainability techniques (SHAP, LIME).

Build and deploy scalable ML models and MLOps pipelines in collaboration with data scientists Required Candidate profile 6–12 yrs in ML development, Python, model tuning, and enterprise AI deployment.

About the Role: Work closely with Enterprise AI Services technical team and architects to establish and deliver Cloud/SaaS based technologies and services including Azure Open AI, AWS Bedrock, Azure API Management, Google Cloud APIGEE, Snowflake, Azure AI Search, Power BI and other emerging technologies to Thomson Reuters product teams. Partner with product development teams to implement best practices and optimize performance of the Enterprise AI and Cloud applications Participate in the analysis of new SaaS, PaaS, and IaaS service, then develop automation and solutions to support using them at enterprise scale Manage cloud service product/feature upgrades, including testing and release planning Research new AI and Cloud technologies and assess maturity and alignment of the technology to business and technology strategy Evaluate and incorporate enterprise-grade security features as standard components of the service offerings we produce, in alignment with Thomson Reuters information security team Prepare and present high quality technical and non-technical documentation Communicate in a professional manner when interacting across staff levels and internal customers Evaluate and communicate risk as a top consideration for all solutions and changes being made on behalf customers About You : Youre a fit for the role of Senior Engineer, Enterprise AI Services , if you have B.S./B.A. Computer Science or related field; or equivalent level of experience Previous Software or Cloud engineering and development experience required UNIX/Linux administration experience required Demonstrated use of programming languages like Python, SQL, C# is an asset AWS Cloud experience (highly recommended, Cloud Practitioner and higher AWS certification preferred) Azure Cloud experience (highly recommended, AZ-900 or AI-900 and higher Azure certification preferred) Google Cloud experience (APIGEE) Understanding of cloud infrastructure. Understanding of non-relational database and search technologies. Understanding of vector capabilities and other AI functions. Demonstrated use of CI/CD technologies is a plus, understanding of tools like Azure DevOps, GitHub, GitHub Actions, JFrog Artifactory, Docker preferred. Strong passion for technology and a willingness to learn new skills Self-motivation and self-direction, ability to translate technical direction and apply to specific work responsibilities Ability to work effectively with cross-functional teams Ability to investigate complex issues spanning multiple technologies Excellent communication (written and verbal) and interpersonal skills Strong technical aptitude Strong analytical skills