Engineering Leader - Applied AI
As an Engineering Leader - Applied AI, you will lead the design and delivery of AI-driven business transformation projects, working directly with customers to understand their needs and translate them into scalable, agent-based AI solutions on the DevRev platform. You will also be responsible for integrating AI agents with external platforms and optimizing their performance, acting as a key connector between sales, customer success, engineering, and product teams.
As an Engineering and Customer facing leader, you will own the end-to-end design and delivery of AI-driven business transformation projects, while also innovating on tools and services on the DevRev product.
You'll work closely with pre-sales teams to scope technical integration and implementation strategies, translating business requirements into architectural solutions. Once opportunities move to post-sales, your team will own the detailed technical designs from original scoping documents and drive execution to build proofs-of-concept, custom integrations, and solutions that validate technical feasibility.
As the technical owner of the customer relationship, you'll partner cross-collaboratively to ensure successful delivery. Your role spans from understanding domain-specific customer needs to designing scalable, agent-based AI solutions using DevRev's platform, with direct involvement in implementing key technical components and debugging complex integration challenges.
This position requires a unique blend of enterprise architecture expertise, AI solution design, hands-on development skills, customer empathy, engineering leadership and cross-functional collaboration. You'll act as the connective tissue between pre-sales, customer success, engineering, and product teams, bringing our AI capabilities to life for real-world business impact.
Coding Skills: Strong proficiency using TypeScript/JavaScript, Python, data structures and algorithms, (Nice to have: Go)
Applied AI Knowledge: Large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
Posted June 2, 2026