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Forter is seeking a Senior Applied AI Engineer to join the AI Engineering team, embedded directly with business functions to drive AI transformation across the organization. This is an outward-facing role where you will partner with GTM and G&A teams—Sales, Marketing, Finance, HR, Legal, Customer Success, and Procurement—to identify and implement high-impact AI solutions that fundamentally change how these teams operate.
You will own the end-to-end lifecycle of AI initiatives: discovering pain points through direct engagement with function leaders, scoping opportunities, building solutions, deploying them, measuring business impact, and iterating based on adoption metrics. You'll serve as the primary technical partner and AI advisor to business leaders, translating their workflows into engineering plans while building their AI fluency. This includes developing hands-on training and enablement for non-R&D teams to use AI tools independently.
You'll operate with significant autonomy, working closely with senior leadership to ensure alignment with company strategy while maintaining visibility across the organization. You'll collaborate with the AI Engineering team to leverage shared infrastructure (MCP servers, RAG systems, evaluation frameworks, guardrails) while feeding back field requirements to improve platform capabilities.
The ideal candidate has 7+ years of software engineering experience with a proven track record of shipping production systems. You have demonstrated success working directly with non-technical stakeholders to deliver technology-driven transformation. You possess exceptional communication skills—equally comfortable running discovery sessions with executives, writing clear briefs, presenting to leadership, and pair-programming on prompt engineering. You think naturally in terms of user problems, adoption, and measurable outcomes rather than technical elegance alone. You're comfortable with ambiguity and self-direction, building your own roadmap by understanding the business. You're passionate about LLMs, prompt engineering, and modern AI application patterns including agentic workflows, RAG, agents, and tool use.
