API Platform: integrating search, retrieval, and AI capabilities into enterprise systems
Perplexity Computer: deploying agentic workflows that operate across tools, applications, and data
Responsibilities
Design, build, and deploy end-to-end integrations between Perplexity and enterprise systems (data platforms, internal tools, SaaS applications), translating business workflows into production-grade AI systems
Work directly with customer teams to embed AI into existing processes, owning deployments from initial architecture through production rollout and ongoing optimization
Develop and operationalize integrations using APIs, event-driven architectures, and workflow orchestration, including deploying Perplexity Computer for multi-step, agent-driven workflows across tools and environments
Design and build production systems that combine retrieval, reasoning, and execution across enterprise environments, applying deep expertise in LLM capabilities, implementation patterns, and the AI stack to drive performance, security, and customer impact
Debug and resolve issues across APIs, infrastructure, and external dependencies, ensuring reliability, performance, and scalability in production
Prototype new integration patterns and build reusable architectures that accelerate adoption across customers
Partner with Sales and Product to unlock new use cases, drive expansion, and translate deployment learnings into product and platform improvements
What we're looking for
5+ years of experience in software engineering, forward deployed engineering, solutions engineering, or similar roles, with a track record of building and shipping production systems in customer-facing environments
Strong programming ability in Python (plus one of JavaScript/TypeScript, Java, etc.) with experience developing integrations, prototypes, and scalable applications
Deep experience with APIs and distributed systems, including authentication, latency optimization, and debugging across complex, multi-system environments
Production experience building LLM-powered systems, including prompt engineering, agent workflows, evaluation, and deploying AI systems at scale
Proven ability to design and implement automated, end-to-end workflows that integrate across enterprise systems and replace manual processes
High ownership and ability to operate in ambiguous environments, with strong system design, rapid prototyping skills, and end-to-end execution
Excellent communication and collaboration skills, with experience working cross-functionally and engaging both technical teams and executive stakeholders
Nice-to-Haves
Experience with search systems, retrieval-augmented generation (RAG), or AI/ML APIs
Background in developer tools, platform engineering, or high-scale/low-latency system design
History of working at startups or small teams, owning customer projects end-to-end
Experience with enterprise IT systems or AI deployment patterns in regulated industries (finance, healthcare, life sciences)
