Forward Deployed Engineer (FDE) Intern

Key Responsibilities

• Under the guidance of Senior FDEs, build and prepare AI agents from scratch for multiple use cases.
• Write, iterate, and optimise the prompts and conversation flows for the Voice and In-App AI Agents, not just the surrounding code.
• Work directly with customer teams to understand technical requirements and constraints.
• Deploy and integrate RevRag AI's Voice and In-App AI Agents into customer environments.
• Write production-ready code for integrations, data pipelines, and custom workflows.
• Test and evaluate agents thoroughly before deployment, validating quality against real scenarios and edge cases.
• Troubleshoot and debug agents in live environments with real user impact.
• Create documentation, runbooks, and hand-off materials for repeatability.
• Surface customer feedback and field signals to influence product direction.

Technical Skills

• Proficiency in Python and core software engineering fundamentals.
• Experience consuming or building REST APIs through projects or coursework.
• Familiarity with web frameworks (Flask, FastAPI, Django) from academic, personal, or internship work.
• Basic understanding of SQL and relational databases.
• Ability to debug issues and reason about system behavior in unfamiliar environments.

AI and LLM Exposure

We do not expect prior production deployment experience; we're looking for strong fundamentals and high learning velocity.

• Foundational understanding of how large language models work and their limitations.
• Curiosity about prompt experimentation using OpenAI, Anthropic, or other APIs.
• Interest in practical evaluation beyond accuracy (reliability, consistency, business impact).
• Willingness to learn model behavior concepts (temperature, tokens, context windows, fine-tuning).

Soft Skills

• Ability to break down ambiguous problems into executable steps.
• Data-driven mindset for validating decisions.
• Strong written and verbal communication.
• High learning agility and comfort with rapid iteration.
• Customer empathy and ability to build trust through technical credibility.

Desired Qualifications

Nice to have, not required.

• Experience with cloud platforms (AWS, GCP, Azure).
• Familiarity with voice AI platforms (Deepgram, ElevenLabs, LiveKit, and similar).
• Understanding of CI/CD pipelines and automation.
• Exposure to containerization (Docker, Kubernetes).
• Background in data engineering or real-time systems.
• Basic frontend exposure (React, TypeScript, Vue).
• Experience in customer-facing technical roles.
• Knowledge of observability and monitoring tools.

What You'll Learn

• How to deploy and optimize frontier AI models in real customer environments.
• End-to-end system design and customer-centric engineering.
• Real-world prompt engineering and LLM performance tuning.
• Translating business requirements into technical solutions.
• Production debugging and performance optimization.
• Customer-facing technical consulting and communication.

Success Looks Like (First 12 Weeks)

• Ship at least one customer-facing integration or workflow.
• Build and validate a proof-of-concept for a real customer use case.
• Document deployment and operational processes for reuse.
• Provide field insights that meaningfully shape product decisions.

This Is a Great Fit If You

• Want hands-on experience with cutting-edge AI and LLM technologies.
• Enjoy solving complex, ambiguous engineering problems.
• Learn new technologies and tech stacks quickly.
• Value real customer impact and seeing your work in production.
• Thrive in fast-moving, collaborative environments.