About the teamThe 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 and services, workflow and process automation, or customization of the DevRev platform 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 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.
About the roleAs a Forward Deployed Architect, you will serve as a hands-on senior technical architect on the Applied AI Engineering team, owning the end-to-end design and delivery of AI-driven business transformation projects.
You will 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, you will own the detailed technical designs from original scoping documents and drive execution - including hands-on coding to build proofs-of-concept, custom integrations, and solution prototypes that validate technical feasibility.
As the technical owner of the customer relationship, you will partner cross-collaboratively to ensure successful delivery. This position requires a unique blend of enterprise architecture expertise, AI solution design, hands-on development skills, customer empathy, and cross-functional collaboration. You will 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.
What you'll do- Customer-Facing: 30-50% working directly with customers
- Coding & Integration: 30-50%+ hands-on technical implementation
- Lead Execution: Define project plans, align internal teams, and ensure timely delivery of deployments
AI-Driven Solution Architecture- Design the detailed AI-driven business transformation, applied AI requirements, and architect the solution needed for customer needs
- Design solutions (AI Agents, Skills, and workflows, etc.) that are aligned with industry best practices, meet the customer needs, and are reusable across other customers
- Create and maintain Applied AI proposals, estimates, solution designs, detailed requirements and measurement framework for KPIs and outcomes
Design & Deployment- Design & 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
- Optimize Performance: Tune prompts, logic, and agent configurations for accuracy, reliability, and scalability
Customer & Cross-Functional- 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
- Advise Customers: Act as a trusted technical advisor on AI agent architecture, performance, and long-term scalability
- Travel Ready: Willingness to travel up to 50% for on-site discovery, deployment, and customer engagement
What you bring- Experience: 5+ years in software development, AI/ML engineering, or technical consulting with customer-facing experience
- Customer Empathy: A bias for action and a relentless focus on solving problems for customers
- Coding Skills: Strong proficiency using TypeScript/JavaScript, Python, data structures and algorithms.
- Communication: Strong written and verbal skills to articulate technical concepts to both engineers and business stakeholders
- Applied AI Knowledge: Large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions. Must be able to articulate AI build experiences, challenges, and trade-offs
- Architecture & Solutioning: Demonstrated experience designing scalable enterprise architecture solutions with security, scalability, and identity management considerations
- Cloud & DevOps: Hands-on experience with AWS, GCP, or Azure at enterprise scale; 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
- Background: Bachelor's or Master's degree in Computer Science, Engineering, or related discipline. Advanced degrees or certifications in AI/architecture frameworks (e.g., TOGAF, SAFe) are a plus
