Forward Deployed Engineer
Advises enterprise customers on AI adoption by identifying use cases, building prototypes, proving business value, and guiding deployment strategy. Requires hands-on customer advisory experience, strong executive communication, enterprise integration knowledge, and solid AI/LLM expertise.
About the job
Responsibilities
- Partner with enterprise customers to identify high-value AI use cases and pilot opportunities.
- Build iterative prototypes to demonstrate measurable value against baseline KPIs.
- Lead executive briefings and translate agentic architectures and AI concepts into business value, ROI, and risk mitigation.
- Support account teams in developing business cases and driving sustained adoption.
- Align engineers, business stakeholders, and executives around a shared technical vision.
- Apply best practices in prompt engineering, LLM selection, tool design, AI governance, and cost control.
- Feed customer learnings into product roadmap development and create repeatable deployment playbooks.
- Maintain current knowledge of AI developments and evangelize data integration, application integration, MCP, and agentic workflow orchestration.
Requirements
- Experience in a customer-facing, hands-on advisory role such as Solutions Architect, Sales Engineer, Field CTO, or equivalent, serving enterprise customers.
- Experience building working prototypes and solutions in ambiguous environments.
- Experience with enterprise data and application integration.
- Understanding of AI/LLM concepts, including prompt engineering, governance, model selection, tool/function design, and cost-performance trade-offs.
- Understanding of evolving AI governance and compliance requirements.
- Strong executive presence and communication skills, with the ability to engage both technical and C-level audiences.
- Ability to coordinate across pre-sales, post-sales, product, and engineering teams.
Preferred Qualifications
- Hands-on programming experience with Python or JavaScript/Node.js.
- Familiarity with LangChain, LlamaIndex, or the Model Context Protocol (MCP).
- Experience with enterprise integration platforms (iPaaS).
- Experience deploying AI or software solutions on AWS, Google Cloud, or Azure.
Skills
Python, JavaScript, Node.js, LangChain, Llamaindex, Model Context Protocol, Ipaas, AWS, GCP, Azure, Prompt Engineering, LLMs, Ai Governance, Application Integration, Data Integration
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