Artificial Intelligence Jobs in St. Louis, MO

Consult with manufacturing clients to analyze processes, identify bottlenecks, and develop strategies to improve speed to market, reduce costs, and enhance quality. Implement lean and Six Sigma methodologies, optimize supply chain integration, leverage digital technologies, conduct feasibility and market analyses, manage project resources, and advise on compliance while building client relationships and developing team leadership skills.

Lead design and implementation of Microsoft Dynamics 365 solutions, supervise and mentor teams, manage project delivery, translate complex requirements into technical designs, handle data migrations and integrations, and build strong client relationships while improving service delivery.

Lead client engagements to optimize manufacturing and product development lifecycles using lean and Six Sigma methods, supply chain integration, PLM, and digital technologies. Manage project planning, budgeting, team coaching, feasibility and cost analyses, and drive adoption of emerging technologies to improve speed to market, reduce cost, and enhance quality.

Supports audit teams with financial assessments, auditing methodologies, compliance and governance projects, data quality validation, research, and audit reporting. The intern also assists with cloud engineering and artificial intelligence solutions that improve audit processes, while developing skills through collaboration, client support, feedback, and observation of experienced auditors.

Leads IT audit engagements assessing digital environments, processes, controls, cybersecurity, data integrity, and AI systems. Manages client relationships, audit teams, project delivery, compliance challenges, data quality validation, governance improvements, and risk management. The role also involves mentoring staff, applying IT governance frameworks, promoting innovative audit technologies, and ensuring assurance standards are met.

Serve as a Microsoft Dynamics 365 functional lead delivering CRM/ERP assessments, design, configuration, fit-gap analysis, data migration, testing, training, and client-facing implementation support. Lead project tasks, create functional requirements and process flows, support proposals and business development, and coach junior staff to deliver solutions leveraging Microsoft platforms.

Lead design and delivery of advanced data and ML solutions, performing exploratory analysis, statistical modeling, and visualization to inform strategy. Manage and coach teams, collaborate with clients to validate outcomes, and improve analytics processes and data quality to drive business decisions.

Lead AI agent build and DevOps workstreams within a data and analytics practice. Manage client accounts and teams, design cloud-based analytics and BI solutions, validate data integrity, develop scalable visualizations (QlikView/Spotfire), and mentor staff to improve data pipelines and client outcomes.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Lead large Microsoft Dynamics 365 (CRM/CE) implementations as a Senior Manager: engage senior clients, design functional solutions, oversee delivery lifecycle, coach teams, refine processes, and ensure operational excellence and adherence to firm standards.

Lead and oversee multiple multidisciplinary teams to architect, develop, deploy, monitor, and maintain full-stack AI solutions (including LLM integrations). Provide strategic and technical leadership, drive experimentation and CI/CD practices, ensure quality and stakeholder alignment, promote innovation, and mentor senior and junior team members to deliver business-aligned AI outcomes.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

Leverage data analytics, business intelligence, and data science techniques to deliver strategic insights and solutions for clients. Build reports, dashboards, data pipelines, visualizations, and data architecture using tools such as Oracle BI, QlikView, Spotfire, and BIRT. Ensure data quality, manage stakeholder relationships, improve analytics processes, interpret complex datasets, and mentor junior team members while contributing to client projects and business strategy.

Design and implement AI-enabled integration solutions, cloud architectures, and enterprise technology platforms. Lead strategic planning, analyze business requirements, conduct feasibility studies, coach teams, manage stakeholders, and validate solutions with clients. Apply generative and agentic AI, IoT, sensor data, systems thinking, and enterprise architecture practices to solve complex business problems and drive innovation.

Lead Microsoft Dynamics 365 CRM implementations, architect solutions, manage project lifecycles and client accounts, mentor teams, ensure quality and post-go-live support, and drive innovation and continuous improvement.

Lead and coach teams to design, develop, and deliver production-grade AI and data solutions for clients. Manage client accounts, ensure quality and timelines, analyze complex datasets, implement best practices, and drive continuous improvement while fostering client relationships and technical excellence.

Build and ship AI-powered digital products from concept through production. Identify high-value AI use cases, develop RAG and agentic systems, select models, apply prompt engineering or fine-tuning, and integrate solutions with enterprise data platforms. Deliver full-stack products with MLOps, monitoring, security, and cost and latency controls. Lead client workstreams, manage senior stakeholders, shape engagements and deals, and codify repeatable delivery practices.

Owns client narratives from discovery through proof of concept, translating business problems into scoped technical solutions. Leads solution design workshops, architecture reviews, RFP responses, estimates, staffing plans, demos, and partner conversations. Carries revenue accountability, supports co-selling, ensures delivery fidelity, develops reusable practice assets, mentors consultants, and builds long-term client relationships. The role requires hands-on technical delivery experience, consulting expertise, AI fluency, partner ecosystem knowledge, and travel flexibility.

Leads complex pre-sales technical engagements for Databricks and cloud solutions, including discovery, architecture, proof-of-concept, TCO modeling, proposals, and SOW scoping. Owns a personal sales target and pipeline while ensuring delivery fidelity. Productizes repeatable offerings, develops reference architectures and pricing models, builds partner relationships, mentors architects, applies AI tools to pre-sales workflows, and supports thought leadership and practice development.

Owns client solution narratives from discovery through proof of concept, translating business problems into scoped technical solutions. Leads presales discovery, architecture workshops, RFP responses, SOW scoping, estimates, staffing plans, demos, and partner co-selling while carrying revenue accountability. Develops AI-focused solution assets, maintains partner relationships, mentors consultants, and ensures delivery fidelity from sale through execution.

Leads enterprise cloud infrastructure, data platforms, on-premises systems, AI enablement, and technology operations. Defines roadmaps, architecture standards, governance, and operational processes while managing technical teams and managers. Drives modernization, automation, platform reliability, security, resilience, cost optimization, and business continuity. Partners with executives, business stakeholders, cybersecurity, compliance, and risk teams to align technology investments with organizational goals and improve execution.

Leads enterprise technology and innovation strategy, cybersecurity, business continuity, AI adoption, Microsoft 365, vendor and MSP relationships, technology budgets, executive reporting, KPIs, and long-term roadmaps. Partners with executive leadership to connect technology investments to growth, efficiency, customer experience, and competitive advantage. Also evaluates emerging technologies and may support SaaS platform management and M&A integration.

Leads tax transformation initiatives by improving and standardizing tax processes, translating business needs into technical requirements, mapping workflows, implementing automation and AI solutions, and supporting project and change management. Partners with tax, IT, BI, and AI teams; evaluates vendors and technologies; facilitates workshops and training; and monitors adoption metrics. Requires individual or partnership tax engagement experience, supervisory experience, and strong knowledge of tax technology and project delivery.