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Deployed Engineer

Location: Palo Alto, CA / San Francisco, CA / New York, NY Company Stage of Funding: Late-Stage / Hypergrowth AI Infrastructure Office Type: On-site Salary: $150,000 – $300,000 + Competitive Equity Visa: Transfers supported case-by-case

Our client is building foundational web infrastructure for AI systems, creating retrieval, ranking, reasoning, and agent interaction systems that allow AI models to consume and interact with web data more effectively.

Founded by former Twitter CEO Parag Agrawal, the company is developing next-generation APIs and infrastructure powering how AI agents access, retrieve, and reason over internet-scale information.

Backed by Sequoia, Kleiner Perkins, and Khosla Ventures with over $230M raised and a reported $2B valuation, the company operates at the frontier of AI infrastructure and web-scale systems.

This is a rare opportunity to join a deeply technical, talent-dense organization and work directly with enterprise customers deploying cutting-edge AI systems into production.

What You Will Do

Own the full technical customer lifecycle from pre-sales to production deployment

Lead technical discovery, demos, POVs, and implementation engagements

Act as the primary technical advisor for enterprise customers

Work directly with Fortune 500 engineering teams

Build evaluation suites, harnesses, and production integrations using Python

Help customers integrate Parallel APIs into AI agent systems

Run technical feasibility workshops and architecture discussions

Serve as the bridge between customer engineering teams and internal product engineering

Debug production issues and support customer deployments

Write production-quality code alongside customer teams

Build and improve agent evaluation workflows

Run and analyze eval suites for AI systems and APIs

Translate customer feedback into product and infrastructure improvements

Become a power user of Parallel's AI search and agent APIs

Support enterprise AI deployments end-to-end

Operate across both technical implementation and strategic customer communication

Travel occasionally for customer engagements and onsite workshops

Work closely with engineering leadership and the CTO

Ideal Candidate Background

2–8 years of experience in Solutions Engineering, Forward Deployed Engineering, or Solutions Architecture

Strong customer-facing engineering experience

Hands-on technical implementation experience

Strong Python proficiency

Experience supporting enterprise or Fortune 500 customers

Ability to write and debug production code

Experience owning technical customer engagements

Strong communication and stakeholder management skills

Comfort operating in highly technical customer environments

Experience running demos, POCs, or implementation workshops

Ability to explain technical systems clearly

Strong problem-solving and debugging capabilities

Comfort with APIs, infrastructure systems, and AI tooling

Ability to balance customer interaction with technical execution

Strong executive presence

Comfort working onsite in fast-paced environments

Interest in AI systems, LLMs, and agent infrastructure

Compensation and Benefits

Base salary: $150,000 – $300,000

Competitive equity package

High-upside AI infrastructure opportunity

Work directly with world-class engineering leadership

Exposure to frontier AI infrastructure problems

Deep enterprise customer ownership

Flat engineering organization

Opportunity to shape customer deployment best practices

Relocation support available

Access to highly technical AI systems work

Direct collaboration with engineering and product leadership

Strong growth trajectory in deployed engineering organization

Why Join

This is an opportunity to work at the intersection of AI infrastructure, enterprise deployment, and customer engineering at one of the best-funded frontier AI infrastructure startups.

You'll help major enterprises deploy next-generation AI systems while working directly on retrieval, reasoning, and agent infrastructure powering the future web for AI.

The role combines deep technical problem-solving, production engineering, customer ownership, and AI systems work in a highly technical environment.

If you enjoy coding, enterprise problem-solving, AI infrastructure, and customer-facing engineering ownership, this role offers exceptional leverage and career growth.