Forward Deployed Engineer (AI)

We're looking for exceptional engineers who enjoy solving complex, real-world problems alongside enterprise customers. As a Forward Deployed Engineer (FDE), you'll work at the intersection of engineering, AI, and customer success, partnering directly with customers to understand their workflows, designing AI-powered solutions, and deploying production-ready AI agents that deliver measurable business impact. This is a hands-on, high-ownership role where you'll take projects from problem discovery to production deployment, working across product, engineering, and customer teams.

Responsibilities:

• Partner directly with enterprise customers to understand business workflows and operational challenges.
• Translate ambiguous business problems into scalable technical solutions.
• Design, build, and deploy AI agents integrated with customer systems and workflows.
• Own end-to-end implementation from architecture and development to deployment and production reliability.
• Validate solutions using real-world data, monitor outcomes, and continuously improve performance.
• Collaborate closely with product and engineering teams to ship high-quality AI capabilities.
• Build reusable tools, documentation, and best practices that accelerate customer deployments.

Requirements:

• 5+ years of software engineering or technical product development experience.
• Strong computer science fundamentals, system design, and problem-solving skills.
• Experience building scalable backend systems, APIs, and integrations.
• Comfortable working across distributed systems, data pipelines, and third-party platforms.
• Ability to thrive in ambiguous environments and independently drive projects to completion.
• Excellent communication skills with the confidence to work directly with enterprise customers.
• Strong ownership mindset with a bias toward execution.
• Passion for building practical AI systems that create real business value.

Nice to Have:

• Experience as a forward-deployed engineer, solutions engineer, implementation engineer, or technical consultant.
• Experience building AI agents, LLM applications, automation platforms, or conversational AI systems.
• Familiarity with MCP, agent frameworks, RAG, workflow orchestration, or enterprise AI deployments.
• Experience operating and improving production systems at scale.
• Exposure to cloud platforms such as AWS, Azure, or GCP.