About the Role
Role details below.
Responsibilities
- Work closely with pre-sales teams to scope technical integration and implementation strategies
- Translate business requirements into architectural solutions
- Own detailed technical designs from original scoping documents and drive execution
- Perform hands-on coding to build proofs-of-concept, custom integrations, and solution prototypes
- Act as the technical owner of the customer relationship
- Partner cross-collaboratively with pre-sales, customer success, engineering, and product teams
- Spend 30–50% of time working directly with customers
- Spend 30-50%+ of time on hands-on technical implementation
- Lead execution by defining project plans, aligning internal teams, and ensuring timely delivery of deployments
- 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.) aligned with industry best practices, meeting customer needs and reusable across other customers
- Create and maintain Applied AI proposals, estimates, solution designs, detailed requirements, and measurement framework for KPIs and outcomes
- Build and configure intelligent solutions leveraging snap-ins, connectors (AirSync), workflows, and AI agents on the DevRev platform
- Connect AI agents with external platforms (e.g., CRMs, APIs, databases) for seamless workflow automation
- Tune prompts, logic, and agent configurations for accuracy, reliability, and scalability
- Partner with customers to deeply understand their needs and translate them into technical agent specifications
- Lead live demos, build rapid proof-of-concepts, and refine solutions through customer feedback
- Act as a trusted technical advisor on AI agent architecture, performance, and long-term scalability
Requirements
- 5+ years in software development, AI/ML engineering, or technical consulting with customer-facing experience
- Strong proficiency using TypeScript/JavaScript, Python, data structures and algorithms
- Strong written and verbal communication skills to articulate technical concepts to both engineers and business stakeholders
- 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
- Demonstrated experience designing scalable enterprise architecture solutions with sec