Customer Engineer, Agent Builder (NYC)

David Joseph & Company

New York (NY)

On-site

USD 175,000 - 230,000

Full time

14 days+

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Benefits offered by this job

Competitive equity
In-office lunches
Comprehensive benefits

Job summary

David Joseph & Company is seeking a post-sales, forward-deployed engineer in New York City to own end-to-end AI agent builds for strategic enterprise customers. The role blends hands-on technical work with customer-facing delivery on a newly formed Agent Builder team.

You will design agent behavior, integrate with customer systems, and communicate with senior stakeholders to align success criteria and timelines. A CS/engineering background and strong Python skills are required.

Qualifications

  • 3+ years in a technical, customer-facing role (solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, or technical product).
  • Strong Python proficiency — comfortable writing code, working with APIs, and building and validating integrations end-to-end (live Python round/case study).
  • Genuine post-sales interest — hands-on technical delivery and customer engagement rather than pre-sales.
  • Exceptional communication skills and executive-ready presence with senior technical stakeholders.

Responsibilities

  • Own end-to-end architecture and execution of AI agent builds for enterprise customers, from design through production deployment.
  • Design and engineer core agentic logic, guardrails, and supervisory controls for safe, compliant performance.

Skills

Python
REST APIs
LLMs/AI agents
Customer-facing delivery
Communication

Education

Computer Science degree

Tools

CRM systems
Ticketing systems
Data pipelines

Job description

New York City, NY
On-site
Full-time
Compensation: $175,000-$230,000 + competitive equity

About The Company

A leading conversational AI platform whose technology lets enterprises deploy AI agents across voice, chat, email, and SMS - replacing support tickets and hold music with faster resolutions and richer conversations. Well-funded and deployed at recognizable consumer and enterprise brands, the company is in-office and built around velocity and technical excellence.

Founded 2023

  • 201-500 people
  • Industry: Conversational AI
  • Customer Support
  • Enterprise SaaS
The Role

A post-sales, forward-deployed engineer who owns end-to-end execution of AI agent builds for strategic enterprise customers - roughly a 50/50 split of hands-on technical build work and customer-facing delivery, on a newly formed Agent Builder team. Ideal for a software or forward-deployed engineer who wants to pivot into customer-facing delivery and thrives in fast-moving, ambiguous environments.

What You'll Be Doing
  • Own end-to-end architecture and execution of AI agent builds for enterprise customers, from systems design and scoping through implementation, evaluation, and production deployment
  • Design and engineer the core agentic logic governing agent behavior, plus layered guardrails and supervisory controls for safe, compliant, predictable performance across non-deterministic outputs
  • Architect, build, and test integrations with customer systems (data pipelines, CRMs, ticketing systems), including the tools, APIs, and workflows needed for reliable deployment at scale
  • Interface with senior technical stakeholders at customers to define success criteria and system requirements, and drive technical delivery against timelines
  • Diagnose, debug, and resolve probabilistic and technical failures through root-cause analysis, and design evaluation and regression-testing frameworks that guard against performance drift
Tech stack:

Python (primary; assessed via a live Python round and case study), REST APIs, LLM / agentic tooling, enterprise integrations (CRMs, ticketing systems, data pipelines)

Requirements
  • 3+ years in a technical, customer-facing role (solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, or technical product)
  • Strong Python proficiency — comfortable writing code, working with APIs, and building and validating integrations end-to-end (assessed via a live Python round and case study)
  • Genuine post-sales interest — wants to go deep on hands-on technical delivery and customer engagement, not pivot toward pre-sales
  • Exceptional communication skills and executive-ready presence, credible with senior technical stakeholders
  • Comfort working in fast-moving, ambiguous environments, shaping solutions as much as implementing them, and available in-office 5 days per week
Green Flags
  • Experience building with or around LLMs and AI agents (prompting, evaluation, guardrails, tooling, workflow design)
  • Experience with enterprise SaaS integrations (ticketing systems, CRM, data pipelines) and associated security and compliance considerations
  • A Computer Science, Engineering, or Math degree, or equivalent technical background (CS strongly preferred; other quantitative degrees such as Data Science or Data Engineering acceptable)
  • Strong product instinct: crisp PRDs, clear success metrics, and customer insight fed back into the product roadmap
Red Flags
  • Background as an IT manager or in IT operations without transferable hands-on technical build experience
  • Interested only in pre-sales work; this role's lane is exclusively post-sales
Why Join
  • Ground-floor role on a newly formed Agent Builder team — you help shape how the company's agents are built, validated, and delivered
  • Genuine technical depth: roughly 50/50 hands-on build and customer-facing delivery, owning agents end-to-end from design through production
  • Strong comp and benefits: competitive equity, take-what-you-need vacation, full medical/dental/vision for you and family, life + disability, retirement plan, parental leave, fertility/family-building benefits, and daily in-office lunches
Details
  • Location — New York City, NY
  • Work policy — In-office 5 days per week
  • Compensation — $175,000-$230,000 + competitive equity
  • Visa sponsorship — H-1B
  • Employment type — Full-time
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