Member Of Technical Staff (Forward Deployed Engineer, Applied AI)
Introduction Perplexity is building AI systems that integrate directly into how enterprises operate. Our API Platform powers search, retrieval, and automation across structured and unstructured data, while Perplexity Computer extends this into the execution of an AI system that navigates tools, interacts with applicati
What this role actually needs.
Introduction Perplexity is building AI systems that integrate directly into how enterprises operate. Our API Platform powers search, retrieval, and automation across structured and unstructured data, while Perplexity Computer extends this into the execution of an AI system that navigates tools, interacts with applicati 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 Requirements: - 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 Company context: Perplexity is an answer engine — an AI-native search product used by millions of professionals daily.
Day-to-day expectations
Perplexity lists these responsibilities for the Member Of Technical Staff (Forward Deployed Engineer, Applied AI) role.
- 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
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 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
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Member Of Technical Staff (Forward Deployed Engineer, Applied AI) is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
United States tech market
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Compensation read
$205K - $335K is visible before the click, so candidates can compare the role against local market expectations before applying.
Work authorization read
Current extracted signal: Open to TN, H-1B, and OPT candidates already in the United States. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
Hybrid roles in New York City should be compared against commute, local salary bands, and nearby employer demand.
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- Show concrete examples of succeeding in hybrid environments.
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Source: jobs.ashbyhq.com · Source ID: aa511ea8-96e3-42ba-b28f-5e222170bcee · Confidence: 94/100 · Last checked: May 7, 2026
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