Forward Deployed Engineer
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A Junior Forward Deployed Engineer works directly with leading organizations to identify, prototype, and deliver AI use cases that create measurable business value. At Reply, your mission is to support customer initiatives across the AI journey, from experimentation to implementation and adoption, working alongside experienced FDEs while progressively developing your technical expertise, customer collaboration skills, and delivery capabilities. WHAT YOU WILL DO
- Turn AI into operational value . Contribute to the journey from AI opportunity identification to production adoption by developing solutions based on foundation models, large language models, retrieval-augmented generation, AI agents, intelligent workflows, and data pipelines.
- Apply AI innovation to real-world needs. Help translate business challenges and emerging opportunities into prototypes and production‑ready features. Participate in rapid experimentation, implementation tasks, and iterative delivery, using real‑world customer feedback to refine and improve solutions.
- Work side by side with customers. Collaborate with business users and engineering teams to understand their challenges, translate needs into actionable technical requirements, and contribute to implementation, deployment, and adoption.
- Connect engineering work to business impact. Contribute to defining and tracking technical and business success metrics, developing an understanding of how engineering decisions influence adoption, operational performance, productivity, risk reduction, and business outcomes.
- Grow within the Forward Deployed Engineering practice. Collaborate with and learn from more senior engineers, share learnings from engagements, and contribute to documentation, playbooks, and reusable assets that support future projects.
- Academic background. A degree in Computer Science, Computer Engineering, or a related field.
- Software engineering and AI foundations. Familiarity with software development and technologies such as generative AI, foundation models, large language models, RAG, and AI agents, gained through academic, personal, or professional projects.
- Customer-facing problem solving. Interest in working directly with customers and users, understanding their challenges, breaking down complex problems, and translating business needs into practical AI solutions.
- Technical curiosity and business orientation. Motivation to deepen your hands-on AI expertise while understanding how technical choices affect adoption, operational performance, and business value.
- Growth mindset and collaboration. A proactive approach to learning, openness to feedback, and the ability to collaborate with cross-functional teams while progressively taking greater ownership.