Customer Engineer, Agent Builder at Pronexus
Location: New York City, San Francisco, or London
Work Policy: 5 days/week in-office
Compensation: $175K–$230K + equity
ProNexus is recruiting for a fast-growing, venture-backed AI company building enterprise AI agents used by leading brands across chat, voice, email, SMS, and other customer communication channels.
This is a Customer Engineer / Agent Builder role, not a traditional software engineering role. You will work directly with enterprise customers to design, build, configure, test, and launch AI agent workflows in production. The ideal candidate is highly technical, strong in Python, polished with customers, and excited to own complex implementation work end to end.
You’ll join a newly formed technical delivery team responsible for building enterprise-grade AI agents that perform reliably at scale. This is a strong fit for someone with experience in forward-deployed engineering, solutions engineering, implementation engineering, technical consulting, customer engineering, or technical support at a complex B2B SaaS company.
What You’ll Do
Own the end-to-end execution of AI agent builds for enterprise customers, from scoping and requirements gathering through launch and iteration.
Build, configure, and validate AI agent workflows, integrations, guardrails, and automation logic.
Write and debug technical implementation artifacts, including Python-based workflows, API integrations, and customer-specific configurations.
Partner directly with senior technical stakeholders at customer organizations to understand requirements, define success criteria, and drive delivery.
Test and validate agent behavior across real-world scenarios to ensure reliability, quality, and business impact.
Work cross-functionally with product, engineering, customer success, and go-to-market teams to improve implementation quality and feed customer insights back into the platform.
What We’re Looking For
5+ years of experience in a technical, customer-facing role at a complex B2B SaaS company. Strong candidates with 3+ years may be considered if they have exceptional technical pedigree and relevant company experience.
Strong Python proficiency and the ability to code, debug, and ship technical work end to end.
Experience working with APIs, integrations, automation workflows, or enterprise SaaS systems.
A track record of delivering technical solutions directly for customers.
Excellent communication skills, especially with technical and executive stakeholders.
Comfort operating in fast-moving, ambiguous environments where you need to structure problems, communicate clearly, and execute quickly.
Bachelor’s degree in Computer Science, Engineering, Math, or a similarly technical field preferred.
Bonus Points
Experience building with or around LLMs, AI agents, conversational systems, prompt workflows, evaluations, or guardrails.
Experience at companies such as Databricks, Snowflake, MongoDB, Google Cloud, ServiceNow, Twilio, Cloudflare, Amplitude, Okta, or similar enterprise SaaS companies.
Experience as a Forward Deployed Engineer, Customer Engineer, Solutions Engineer, Implementation Engineer, Technical Account Manager, or technical support engineer for a highly technical product.
Experience with enterprise integrations such as ticketing systems, CRMs, internal tools, or workflow automation platforms.
Important Role Expectations
This is not a software engineering role and does not have a path into a traditional SWE position.
This role is highly customer-facing and implementation-focused.
Candidates must be willing to work 5 days per week in-office in NYC, SF, or London.
Candidates must be willing to complete a 3-day case study as part of the interview process.
The interview process includes a live technical coding round, preferably in Python.
Why This Role
You’ll join a high-growth AI company backed by top-tier investors and working with major enterprise customers.
You’ll be part of a brand-new team with the opportunity to help define how enterprise AI agents are built and deployed in the real world.
You’ll work at the intersection of engineering, customer delivery, AI workflows, and enterprise product implementation.
You’ll get hands-on experience building production AI systems for large-scale customers, not just demos or prototypes.