Applied AI Leader

The Applied AI Engineering team ensures our customers get the optimal experience from DevRev. As customers go through their DevRev journey, they may identify needs for integration with existing enterprise systems/services, workflow/process automation or customisation/enhancement of the DevRev platform capabilities to achieve their business objectives.
Our team works with customers to understand requirements and design, develop, and implement solutions to meet customer goals. Your mission is to systematically help customers find value with DevRev by developing a thorough understanding of their needs, owning the coordination between internal and external stakeholders, and engineering the solution to get the job done. You are a product expert and will use your application development and AI/ML skills to ensure our customers get the most out of the DevRev platform.
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.
Requirements:
Customer-facing: Working directly with customers.
Lead Execution: Define project plans, align internal teams, and ensure timely delivery of deployments.
Design and Deploy AI Agents: Build and configure intelligent solutions leveraging snap-ins, connectors (AirSync), workflows, and AI agents on 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.
Optimise 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 and Iterate: Lead live demos, build rapid proofs-of-concept, and refine solutions through customer feedback.
Advise Customers: Act as a trusted technical advisor on AI agent architecture, performance, and long-term scalability.
Travel Ready: Willingness to travel up to 30% for on-site discovery, deployment, and customer engagement.
Requirements:
Experience: 5+ years in software design and development, AI/ML engineering, or technical consulting, coupled with customer-facing experience.
Leadership: 3+ years leading technology teams as a hands-on leader.
Customer Empathy: A bias for action and a relentless focus on solving problems for customers.
Communication: Strong written and verbal skills to articulate technical concepts to both engineers and business stakeholders.
Cloud and DevOps: Hands-on experience with AWS, GCP, or Azure and modern DevOps practices (CI/CD, containers, and 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.
Background: Bachelor's or master's degree in computer science, engineering, or a related discipline. Advanced degrees or certifications in AI/architecture frameworks (e. g., TOGAF, SAFe) are a plus.
Nice to have:
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.

Experience
13-17 yrs