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Enterprise AI Architect

Role overview

Qualifications

  • Architect-level experience with proven ownership of real systems
  • Strong engineering foundation in at least one modern stack (TypeScript / Node.js, Python, Java or .NET)
  • Direct experience with external clients and senior business stakeholders
  • Presales experience: shaping, scoping, estimating and pitching solutions

Responsibilities

  • Work with senior business stakeholders to define objectives and outcomes
  • Own the technical shape of the whole capability, including standards and shared components
  • Design, build, test and maintain reusable AI skills
  • Run pilots with real users, collect feedback and ship improved versions

Key facts

Hard skills

Other skills

  • Consulting
  • Problem Solving
  • Communication

About the company

Bonapolia logo

Bonapolia

Staffing & Recruiting

BONAPOLIA is a staffing company offering augmentation and recruitment services to place the right people with the right jobs in the USA, Europe, and Scandinavia. Whether you are looking to hire new staff or find a new job, we’re happy to offer you our services. Contact us up to arrange an appointment. We’ll have your hiring or job-seeking needs met in no time by one of our professional team members.

Company details

Company typeScaleup
IndustryStaffing & Recruiting
Company size11 - 50

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Job description

About the role
We are looking for an Enterprise AI Architect to own the technical shape of an enterprise AI capability for our client. You will work directly with senior business stakeholders, decide what is worth automating, design and build reusable AI skills, and lead a small team of two Lead AI Solutions Engineers. This is a hands-on architecture role with a strong consulting and presales component.

What you will do

Shape the work

  • Work with senior business stakeholders and domain experts to define objectives, constraints and expected outcomes

  • Identify which processes are worth automating and which are not, and say so when the answer is no

  • Select tools, platforms and approaches for each business problem and defend the choice to both technical and business leadership

  • Shape and present solution proposals: scope, approach, effort, expected impact

  • Own outcomes with a product mindset: adoption, measurable time saved, reliability for real users

Own the architecture

  • Own the technical shape of the whole capability: standards, shared components, evaluation and release strategy, backwards compatibility

  • Define what a well-formed skill looks like, what belongs in shared infrastructure and what gets rejected in review

  • Make and justify platform-level decisions: agent harnesses, integration architecture, build vs adopt

  • Apply sound judgement on data handling, security and compliance when working with sensitive HR and compensation data

  • Provide technical leadership to two engineers: review, direction, unblocking

Build it

  • Design, build, test and maintain reusable AI skills: instructions, scripts, validation logic, reference data, shared components

  • Write and review production-quality code and own it through review, CI and release

  • Build the evaluation layer: golden cases, acceptance criteria, regression checks

  • Debug agent behaviour and fix root causes

  • Integrate with the client’s platforms and data sources

Drive it forward

  • Run pilots with real users, collect structured feedback and ship improved versions

  • Set and enforce standards for authoring, reviewing, versioning and releasing skills

  • Track where AI tooling is going and bring relevant parts into the engagement early

Must have

  • Architect-level experience with proven ownership of real systems: module boundaries, reuse, versioning, integration, non-functional requirements

  • Still hands-on: you write and review production code today

  • Strong engineering foundation in at least one modern stack (TypeScript / Node.js is a plus, Python, Java or .NET backgrounds are welcome)

  • Solid engineering practice: version control, code review, automated testing, CI/CD

  • Real LLM-backed systems shipped to real users, not just prototypes

  • Broad hands-on knowledge of the current AI tooling landscape, not tied to a single vendor

  • Working command of agentic patterns: tool use / function calling, MCP, prompt and context engineering, orchestration

  • Experience evaluating non-deterministic systems with test sets and measurable acceptance criteria

  • Judgement on where AI fits and where conventional software is the better answer

  • Direct experience with external clients and senior business stakeholders, including CTO-level conversations

  • Presales experience: shaping, scoping, estimating and pitching solutions

  • Ability to turn ambiguous requirements into a clear design and work without a full specification

  • English C1

  • Sustained working-hours overlap with US / Western Europe

Nice to have

  • Hands-on experience with Claude Code, especially authoring Skills, plugins or MCP servers

  • LLM evaluation tooling (promptfoo, LangSmith, custom harnesses)

  • Consulting or professional services background

  • Exposure to HR tech, compensation & benefits, payroll or workforce analytics

  • Experience building internal developer tooling or a platform capability

  • Public work: open-source agent tooling, published skills or plugins, talks, technical writing


πŸ“© Ready to Join?
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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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