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Perplexity information

What is a perplexity job?

Perplexity jobs typically refer to roles at Perplexity AI, a company specializing in artificial intelligence-powered search engines and conversational AI tools. Employees may work in a variety of positions such as software engineering, research, product management, and data science. Perplexity AI is known for its focus on creating advanced, user-friendly AI systems that help people access and understand information more easily. Working at Perplexity often involves collaborating on innovative projects, leveraging the latest AI technologies, and contributing to the development of cutting-edge products in the AI space.

What are the key skills and qualifications needed to thrive as a Perplexity AI Engineer?

To thrive as a Perplexity AI Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree and hands-on project experience. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and version control systems like Git is essential. Strong problem-solving abilities, collaboration, and effective communication help you excel in multidisciplinary teams and adapt to evolving technologies. These skills are crucial for developing advanced AI solutions and ensuring they perform reliably and ethically in real-world applications.

What are the common challenges faced by a data scientist when working on machine learning projects within a cross-functional team?

Data Scientists often encounter challenges such as aligning project goals across departments, ensuring data quality, and effectively communicating complex technical concepts to non-technical stakeholders. Collaborating with product managers, engineers, and business analysts requires strong interpersonal skills and adaptability. Additionally, balancing experimentation with project deadlines and integrating models into production systems are key hurdles. Navigating these challenges successfully can lead to impactful solutions and professional growth.

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Perplexity jobs near you
Infographic showing various Perplexity job openings in Dublin, CA as of August 2026, with employment types broken down into 1% Internship, 90% Full Time, 6% Part Time, and 3% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution.

Forward Deployed Engineer, Perplexity Computer

Perplexity

San Francisco, CA • On-site

$200K - $250K/yr

Full-time

Posted 11 days ago

Job description

Perplexity is seeking a highly skilled and motivated Forward Deployed Engineer to ensure our customers are getting the most out of their Perplexity Computer deployments. This role is ideal for technical, consultative professionals who have driven complex software implementations for bleeding edge customers.
About the role
Perplexity Computer is a new class of AI system that navigates tools, interacts with applications, and completes multi-step enterprise workflows end-to-end. Our largest customers are Fortune 500 enterprises, top consulting firms, and frontier finance and legal shops. They are betting on Computer to automate work where no traditional software has ever succeeded.
Forward Deployed Engineers (FDEs) are the people we embed with customers to scope their highest-leverage use cases, and ship a working solution at velocity. You will leave your customers with something that drives measurable impact.
This is not a Solutions Engineer role, not a Customer Success role, and not a generalist implementation role. It is a customer-embedded, hands-on-keyboard, outcome-owning role that sits at the intersection of engineering, solutions architecture, and technical program management.
What you'll do
  • Embed with strategic customers on time-boxed engagements (typically 1-3 months) running the engagement like a project with clear scope, milestones, and exit criteria.
  • Design and build the workflow with support from engineering as needed. You will be hands-on-keyboard in Computer and adjacent tooling. You will prototype, ship, debug, and harden the solution in the customer's environment.
  • Own the customer relationship for the duration of the engagement: manage expectations with executive sponsors, run weekly working sessions with practitioner teams, and de-risk the deployment end-to-end.
  • Turn every engagement into leverage. Deployments should produce a reusable skill, connector, workflow template, or reference implementation that our next customer, our GTM team, or our Product team can build on.
  • Partner with Sales and Customer Success on scoping, pre-sales technical validation, and expansion. You are the technical voice in the room for our highest-value opportunities.

What we're looking for
The best FDEs we've seen are roughly ⅓ engineer, ⅓ customer-facing solutions architect, ⅓ services-oriented program manager. You should be excellent at at least two of the three and credible in all three.
Must-haves
  • 5+ years in a customer-embedded technical role: forward-deployed engineering, senior solutions engineering, solutions architecture, or technical consulting at a strong services organization.
  • Proven track record running customer engagements as projects: scoping, milestones, status, executive comms, risk management, exit criteria. You have said "no" and "not yet" to customers and made it stick.
  • AI-native. You use frontier LLMs, agents, and coding assistants daily and have strong intuition for what current models can and cannot do reliably.
  • Executive-credible communication. You can walk a CIO through architecture in a credible way while running the program on the ground as well.
  • High agency in ambiguity. No PM, no spec, no perfect requirements. You go in, figure out what matters, and ship.

Nice-to-haves
  • Prior FDE, applied-AI, or deployment-strategist role at a frontier AI company
  • Sales Engineering leadership at an enterprise SaaS or infra company where you owned the technical outcome of $1M+ deals
  • Solutions Architect in a strong services team
  • Experience deploying agents, RAG systems, or multi-step LLM workflows in a regulated or complex enterprise environment
  • History of working at startups or small teams, owning customer projects end-to-end

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