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DevRev is building Computer, an AI teammate platform that unifies data sources, tools, and workflows into a single AI-ready system. The company has raised $150M+ from Khosla Ventures and Mayfield and is trusted by global enterprises.
As a Forward Deployment Architect on the Applied AI Engineering team, you will serve as a hands-on senior technical architect owning end-to-end design and delivery of AI-driven business transformation projects. 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, you'll own detailed technical designs 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'll partner cross-functionally to ensure successful delivery. Your role spans understanding domain-specific customer needs to architecting scalable, agent-based AI solutions using DevRev's platform, with direct involvement in implementing key technical components and debugging complex integration challenges. You'll act as connective tissue between pre-sales, customer success, engineering, and product teams.
Key responsibilities include: designing and deploying intelligent agents using the DevRev platform; integrating AI agents with external platforms (CRMs, APIs, databases) for seamless workflow automation; tuning prompts, logic, and agent configurations for accuracy and scalability; partnering with customers to understand needs and translate them into technical agent specifications; leading live demos and building rapid proofs-of-concept; defining project plans and ensuring timely delivery; and acting as a trusted technical advisor on AI agent architecture and long-term scalability. The role is 80% customer-facing.
REQUIREMENTS:
- 7+ years in software development, AI/ML engineering, or technical consulting (customer-facing experience a plus)
- Bachelor's or Master's degree in Computer Science, Engineering, or related technical field
- Strong proficiency in TypeScript/JavaScript and Python; solid understanding of data structures and algorithms (Go is nice-to-have)
- Applied AI knowledge: Large language models (LLMs), prompt engineering, frameworks like RAG and function calling, building evals for agentic AI solutions
- Hands-on experience with AWS, GCP, or Azure and modern DevOps practices (CI/CD, containers, observability)
- Comfortable integrating systems via APIs, webhooks, and event/data pipelines
- Data-driven mindset: use A/B testing, telemetry, and metrics to guide decisions
- Strong written and verbal communication skills to articulate technical concepts to engineers and business stakeholders
- Customer empathy with bias for action and relentless focus on solving customer problems
- Advanced degrees or certifications in AI/architecture frameworks (e.g., TOGAF, SAFe) are a plus
