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.
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
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
Forward Deployed Engineer background
Solutions Architect experience at top-tier infrastructure companies
Experience at Snowflake, Databricks, MongoDB, Datadog, Palantir, Stripe, Twilio, etc.
Enterprise AI infrastructure experience
Customer-facing engineering ownership
Hands-on API implementation experience
Technical pre-sales and post-sales deployment experience
Experience running evaluation frameworks and agent harnesses
Strong debugging skills
Experience working directly with enterprise engineering teams
Strong Python engineering background
AI infrastructure curiosity and technical fluency
Enterprise deployment ownership
Strong communication with executive stakeholders
Ability to navigate both technical and business conversations
Experience supporting production AI systems
Customer engineering or technical account leadership
Hybrid technical + customer-facing mindset
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
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.
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