DevRev is hiring a Forward Deployed Engineer - Applied AI

About the Role

Role details below.

Responsibilities

• Work closely with pre- and post-sales Customer Experience team by developing solutions over the core platform via applications written in TypeScript, JavaScript, Python, etc.
• Build the Knowledge Graph that includes integration of DevRev with other SaaS and non-SaaS systems through webhooks and APIs and/or real-time communication architectures.
• Employ creativity and expertise to ideate and shape how AI, analytics and workflows are used in customers' processes.
• Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers' existing tech stacks and workflows.
• Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow.
• Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy and user experience.
• Write SQL queries, perform data analysis, and build dashboards to surface insights that drive customer decision-making.
• Develop rapid proofs-of-concept, conduct live technical demos, and refine solutions based on customer and stakeholder feedback.
• Maintain constant communication loops with customers, engineering, product, customer success, support, and revenue teams to ensure alignment.
• Learn and master new tools, then guide customers through critical workflows like code repository integrations and advanced configurations.
• Willingness to travel up to 30% for on-site implementations, technical workshops, and customer engagements.

Requirements

• 5+ years in software development, systems integration, or platform engineering.
• Strong proficiency in TypeScript, JavaScript, Python, data structures and algorithms.
• Build and configure intelligent solutions leveraging snap-ins, connectors (AirSync), workflows, and AI agents on the DevRev platform to solve real customer problems.
• Familiarity with large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
• Deep experience with large-scale data synchronization (one-way and two-way), API integration patterns (REST, GraphQL, webhooks), and event-driven/pub/sub architectures.
• Hands-on experience deploying on serverless and edge platforms (AWS Lambda, Google Cloud Functions) with modern DevOps practices (CI/CD, containers, observability).
• Skilled in data mapping, schema alignment, and working with heterogeneous systems.
• Understanding of data modeling and graph data structures.
• Experience implementing clear logging, actionable error surfacing, and telemetry to support faster debugging and issue resolution.
• Familiarity with Model Context Programming (MCP) for building adaptive, context-aware integrations.
• Strong written and verbal communi