Gruve

AI Engineer

• Work directly with business stakeholders to map workflows, pain points, and current-process costs
• Benchmark industry standards, regulations, and best practices using AI research tools
• Define problems, scope, success measures, and delivery dates; push back when scope does not fit the timeline
• Build and demo working proofs of concept within the first couple of days
• Iterate live with users and decide whether to pivot, phase, or stop
• Develop full-stack web apps, AI agents, workflow automations, integrations, and data pipelines
• Write specifications and prompts, break work into AI-executable tasks, run parallel agents, and review and correct output
• Use AI to generate tests, review code, find bugs, and produce documentation
• Build reusable prompts, skills, templates, and components
• Prepare information security, data privacy, and legal documentation
• Manage change requests through the change control process
• Deploy to enterprise cloud environments with SSO, role-based access, logging, monitoring, and cost controls
• Train users, produce user and support guides, and obtain business sign-off
• Run several projects concurrently on staggered timelines with fixed completion targets
• Track work daily and raise risks and blockers promptly

Explore AI Engineer – Full-Stack at Gruve. Review requirements and application details.

AI Engineer – Full-Stack

Business Analyst

• Lead and drive digital transformation and M&A initiatives across the enterprise, from discovery through delivery
• Gather, analyze, and document business requirements from internal and external stakeholders
• Translate business requirements into functional specifications, user stories, and process workflows
• Analyze business processes and recommend technology-driven improvements
• Identify and evaluate process optimization opportunities using Generative AI, AI agents, and workflow automation
• Prepare business cases, solution proposals, executive presentations, and project documentation
• Define project KPIs, track delivery against business objectives, and report progress to leadership
• Identify, assess, and mitigate project risks and dependencies across cross-functional teams
• Support Agile ceremonies, including sprint planning, backlog prioritization, and user acceptance testing (UAT)
• Build relationships with business and engineering stakeholders to ensure alignment and adoption
• Stay current on emerging AI technologies and industry best practices, and share insights with the wider team

Explore Senior Business Analyst – Digital Transformation, AI at Gruve. Review requirements and application details.