AI Practitioner / Forward Deployed Engineer
ahead-gmbh
| Company | ahead-gmbh |
| Category | Engineering |
| Location | US |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 24 Apr 2026 |
| Last verified | 12 Aug 2026 |
| Source | The employer's own careers page (company_site) |
Description
The AI Practitioner (Enterprise GPT Platform) is a hands-on, customer-facing role on the Enterprise Insights & GPT Platform team at AHEAD. You will design, build, and run production AI applications on our Enterprise GPT Platform — custom agents, workflows, connectors, and integrations — that fundamentally transform the way AHEAD does work. You'll orchestrate our platform with best-in-class AI tools and emerging technologies to create a cohesive, scalable AI ecosystem. You own the full solution lifecycle: discovery, design, build, rollout, and ongoing optimization.
What You'll Do:
• Build on the Enterprise GPT Platform, designing, implementing, and deploying custom AI agents, workflows, connectors, and integrations.
• Orchestrate the platform with best-in-class AI tools and emerging technologies to create a cohesive, scalable AI ecosystem.
• Own the full solution lifecycle: discovery, design, build, rollout, and ongoing optimization.
• Work directly with business stakeholders to identify opportunities and translate them into production-ready AI solutions.
• Monitor, evaluate, and continuously improve AI systems in production.
Required Experience:
• Bachelor's degree in Computer Science, Engineering, Information Systems, Data/Analytics, or equivalent experience.
• Hands-on experience building and deploying AI applications, including custom agents, retrieval-augmented generation (RAG) pipelines, and LLM-powered workflows.
• Familiarity with agent and orchestration frameworks (e.g. LangChain, LangGraph, AutoGen).
• Strong software engineering fundamentals.
• Experience with cloud infrastructure, APIs, and integration development.
• Excellent communication skills to engage with both technical and non-technical stakeholders.
How You Work:
• Operate as a builder and advisor, not just an implementer.
• Thrive in ambiguous environments and take ownership end-to-end.
• Continuously learn and adapt to new AI technologies and patterns.