Forward Deployed Engineer - Architect

Summary

Join DevRev as a Forward Deployed Engineer - Deployment Architect and build, configure, and launch intelligent agents using the DevRev platform to solve real customer problems. Integrate AI agents with external platforms, optimize performance, and partner with customers to understand their needs. Lead live demos, build proof-of-concepts, and refine solutions through customer feedback. Define project plans, align internal teams, and ensure timely delivery of deployments. Act as a trusted technical advisor on AI agent architecture, performance, and scalability. This role requires strong proficiency in Python and/or Golang, familiarity with LLMs and prompt engineering, and experience with cloud platforms and DevOps practices. The ideal candidate will possess a data-driven mindset and excellent communication skills.

Requirements

• Background : Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• Experience : 3+ years in software development, AI/ML engineering, or technical consulting. Customer-facing experience a plus
• Coding Skills : Strong proficiency in Python and/or Golang. Clean, maintainable code is your default
• Applied AI Knowledge : Familiarity with large language models (LLMs), prompt engineering, and frameworks like RAG and function calling
• Cloud & DevOps : Hands-on experience with AWS, GCP, or Azure, and modern DevOps practices (CI/CD, containers, observability)
• System Integration : Comfortable integrating systems via APIs, webhooks, and event/data pipelines
• Data-Driven Mindset : Use A/B testing, telemetry, and metrics to guide decisions and drive improvements
• Communication : Strong written and verbal skills to articulate technical concepts to both engineers and business stakeholders
• Customer Empathy : A bias for action and a relentless focus on solving problems for customers

Responsibilities

• Design & Deploy AI Agents : Build, configure, and launch intelligent agents using the DevRev platform to solve real customer problems
• Integrate Systems : Connect AI agents with external platforms (e.g., CRMs, APIs, databases) for seamless workflow automation
• Optimize Performance : Tune prompts, logic, and agent configurations for accuracy, reliability, and scalability
• Own Requirements : Partner with customers to deeply understand their needs and translate them into technical agent specifications
• Prototype & Iterate : Lead live demos, build rapid proof-of-concepts, and refine solutions through customer feedback
• Lead Execution : Define project plans, align internal teams, and ensure timely delivery of deployments
• Advise Customers : Act as a trusted technical advisor on AI agent architecture, performance, and long-term scalability