Top Tech Jobs & Startup Jobs in Austin, TX

Leads client discovery, requirements gathering, functional design, and configuration of Microsoft Dynamics 365 and Power Platform solutions. Translates business objectives into user stories, process flows, workflows, and solution requirements; conducts functional testing and supports user acceptance testing. Manages functional workstreams, risks, dependencies, and deliverables while serving as liaison between clients and technical teams. Supports adoption through demonstrations, training, documentation, and knowledge transfer, while mentoring junior staff and applying AI tools to delivery.

Lead and support Workiva GRC technology implementations for clients, including requirements gathering, solution design, configuration, testing, training, deployment, and ongoing support. Serve as a Workiva subject matter expert, translate business needs into technical solutions, support demonstrations and proofs of concept, and contribute to project leadership, client service, and business development.

Lead post-go-live optimization for Microsoft Dynamics 365 Supply Chain Management environments. Assess configuration and adoption across inventory, procurement, warehousing, planning, and related modules; identify business pain points; create enhancement roadmaps; guide system configuration changes; and apply AI and Copilot automation opportunities. The role also includes client and executive stakeholder engagement, relationship expansion, methodology development, mentoring, backlog management, and practice growth.

Supports consulting clients in identifying, prioritizing, and implementing Generative AI solutions. Responsibilities include facilitating workshops, analyzing requirements and processes, supporting proof-of-concepts, exploring data, developing documentation, testing solutions, tracking project plans, translating business needs into technical specifications, and delivering GenAI training. The role emphasizes Microsoft AI technologies, prompt engineering, Agile and SDLC practices, continuous AI learning, and client collaboration.

Designs and delivers enterprise solutions across Dynamics 365, Power Platform, Dataverse, Azure, and DevOps. Responsibilities include application and integration architecture, hands-on prototyping, code and configuration reviews, troubleshooting, ALM standards, CI/CD pipelines, testing, security, governance, technical workshops, go-live support, proposals, delivery planning, and mentoring. The role requires technical leadership across full-cycle Dynamics 365 implementations and close client collaboration.

Lead post-go-live optimization for Microsoft Dynamics 365 Finance clients. Assess production environments, identify configuration and adoption gaps, prioritize enhancement roadmaps, manage backlogs, and guide design, testing, and releases. Advise finance and operations leaders, improve data integrity and user experience, identify Copilot and agentic AI opportunities, review engagement quality, mentor consultants, and contribute to consulting methodologies and practice growth.

Lead HCM/payroll implementations for public sector clients: gather requirements, run workshops, design/configure systems, write user stories, support testing/reconciliation, mentor analysts, deliver documentation and presentations, and support proposals and client relationships using Agile methods.

Support IT advisory engagements by gathering requirements, executing project tasks, assisting stakeholder communication, aiding change management, participating in IT due diligence, and supporting IT strategy, system selection, PMO activities, and M&A integration under senior supervision.

Summer data science internship working on ML projects (anomaly detection, numerical optimization, PII/PHI NLP). Interns will develop models, write high-quality Python, use Linux and development tools, work with git, Docker, CI/CD and Kubernetes, participate in code reviews and agile rituals, and present results to technical and non-technical audiences.

Develop and productionize AI features from PoC to scalable deployments. Write production-ready Python code, implement testing and debugging, refine user stories, participate in ethical and security reviews, and collaborate with stakeholders to align AI solutions with business needs.