Abdul Rafay Admin

Ignitium: ABX Orchestration

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 About the Role
 
 
 
 We&rsquo;re looking for a hands-on Applied AI Engineer to build the AI tools, agents, and automations that make Ignitium faster, and increasingly, to build custom AI solutions and PoCs for our clients.
 
 
 This is a true individual contributor role in a complex environment. Our work spans dozens of interconnected systems: workflow platforms (n8n, Clay, Zapier, Make), data and BI tools (BQ, CloudSQL, Domo, Google Sheets), project management (Asana), enrichment and outbound tools (Outreach,
 
 Ora.im
 
 ,
 
 Apollo.io
 
 , Zoominfo, SalesLoft, Sales Navigator), intent data (Bombora, 6sense, Demandbase), ad platforms (LinkedIn, Meta, Google, Reddit, X), and a growing AI layer of Agents, MCP servers, custom skills, and browser automation. No two clients look alike and the problems are rarely well-defined when they reach you.
 
 
 AI-assisted development: We expect you to use AI coding tools aggressively. They&rsquo;re core to how we work. AI assistance multiplies engineering skill, it doesn&rsquo;t replace it. You must be able to read, debug, and own what you ship.
 
 
 
 Key Responsibilities
 
 
 
 
 Internal AI Tools &amp; Automations (core of the role)
 
 
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 Design, build, and maintain AI-powered tools, agents, and workflows used daily by internal teams.
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 Build integrations across our stack: n8n workflows with custom code, MCP servers, APIs, webhooks, and browser automation for systems without APIs.
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 Translate ambiguous business problems into solutions with clear inputs, outputs, and success metrics.
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 Harden what you build: error handling, logging, monitoring, and graceful failure for unattended workflows.
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 </ul>
 
 
 Client-Facing PoCs &amp; Custom Builds
 
 
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 Build custom AI solutions, demos, and PoCs for client needs, adapting internal patterns to client data and systems.
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 Prototype rapidly, evaluate against real data, and iterate.
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 Document PoCs and support hand-off into productionized implementations.
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 </ul>
 
 
 AI Platform &amp; Best Practices
 
 
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 Work fluently with LLM APIs (Anthropic, OpenAI) and agentic tooling (Agent SDKs, MCP, skills).
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 Apply best practices for context design, model selection, evaluation, guardrails, and data handling.
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 Contribute reusable components and patterns so every build makes the next one faster.
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 </ul>
 
 
 Collaboration
 
 
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 Partner with non-technical stakeholders to surface pain points worth automating.
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 Explain trade-offs (cost, latency, accuracy, reliability) in plain language.
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 </ul>
 
 
 Required Qualifications
 
 
 
 
 Engineering Fundamentals (non-negotiable)
 
 
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 Strong coding competency in
 
 TypeScript/JavaScript and/or Python
 
 . You can build, debug, and maintain real software without an AI assistant, even though you&rsquo;ll rarely work without one.
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 Deep comfort with APIs, webhooks, auth, JSON, and integrating SaaS systems that were never designed to talk to each other.
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 Solid practices: Git, testing and debugging discipline, and an instinct for when a quick script is fine versus when something needs to be built properly.
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 Proven ability to take a vague request and ship a working solution end-to-end.
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 </ul>
 
 
 Applied AI Experience
 
 
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 Hands-on experience building production (or production-like) applications with AI integration.
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 Working knowledge of prompt and context engineering, RAG, structured outputs, tool use, and agent architectures.
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 Experience with a workflow automation platform (n8n preferred; Zapier or Make also valued), including writing custom code inside it.
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 Understanding of model trade-offs: latency, cost, accuracy, and when a cheaper model is the right call.
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 </ul>
 
 
 Soft Skills
 
 
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 Bias toward action. You&rsquo;d rather ship a v1 this week than design a perfect system next month.
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 Comfortable breaking fuzzy problems into small, testable steps.
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 Clear written and verbal communication with non-technical stakeholders.
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 </ul>
 
 
 Nice to Have
 
 
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 Building or consuming MCP servers, or working with the Claude Agent SDK or agentic frameworks.
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 Browser automation (Browserbase, Stagehand, Playwright, Puppeteer, or agent-driven browsing).
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 Vector databases, search systems, or LLM evaluation frameworks.
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 Background in B2B SaaS, GTM operations, RevOps, ABM/ABX, or agency environments.
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 What Success Looks Like (First 12 Months)
 
 
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 Multiple internal AI tools shipped, actively used, and trusted, with stakeholders able to point to hours saved or quality gains.
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 Client-facing PoCs and custom builds that helped win, retain, or expand client relationships.
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 Automations that keep working: they fail loudly, recover gracefully, and don&rsquo;t need babysitting.
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 A growing library of reusable components and patterns that others can build on without you in the room.
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 </ul>
 
 
 
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Applied AI Engineer

Join Ignitium: ABX Orchestration and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Ignitium: ABX Orchestration

About Company

Applied AI Engineer