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AI Transformation and Enablement Manager

Delveaccount · Warsaw, Mazowieckie, 01-211, Poland · Hybrid · Active · BambooHR

Job facts

FieldValue
CompanyDelveaccount
TitleAI Transformation and Enablement Manager
Normalized title-
Department / team-
LocationWarsaw, Mazowieckie
Work modelHybrid / Hybrid
Employment typeContract
Salary-
Statusactive
ATS providerBambooHR
Posted / first seen2026-03-24 / 2026-05-30
Changed / last seen2026-05-30 / 2026-06-06

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Work model jobsActive Hybrid postings.Open
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Linked records

CompanyDelveaccount
Source9b0564fb-de43-40fa-a0ec-45fe8a64c6db
ATS providerBambooHR

Description

WHO WE ARE Delve Deeper is a performance media agency focused on the charity and nonprofit sector, partnering with organizations that invest $5M–$20M annually in media. We help mission-driven teams maximize impact through advanced digital strategies that drive measurable, scalable results. Our expertise includes advanced analytics, intent-based audience segmentation, full-service media management, and personalized creative—delivering a fully integrated, data-driven approach to growth. More than a vendor, we serve as a strategic partner, helping organizations solve complex media challenges and turn them into clear outcomes. With decades of leadership experience, Delve Deeper is a trusted voice in the charity space. We’ve also been named Built In Colorado’s “Best Places to Work” for five consecutive years, reflecting a culture that values performance, growth, and people. As a privately owned company, we move quickly, support our team holistically, and create meaningful opportunities for advancement. ROLE OVERVIEW You are accountable for making AI work across the agency — in practice, at scale, producing results people can feel. The foundation of this role is a rigorous understanding of how the business actually operates: where time goes, how decisions get made, where information stalls, and which processes are ripe for change. This role has two connected areas of ownership. The first is fast, iterative workflow automation: mapping processes analytically, identifying where the agency is losing time, and getting working solutions built and adopted quickly via n8n. The second is broader AI enablement: identifying where the right AI tool — applied to the right operational problem — can change how the agency stores knowledge, surfaces information, or supports decisions. Both areas start from the same place: a clear-eyed read of how work actually flows. This person brings business operations experience and process mining skills to that analysis — the ability to observe a workflow, decompose it analytically, identify where value is being lost, and design the right intervention. AI is the toolkit. Business acumen is what determines where to point it. Speed and judgement are the twin engines of the role. On the automation side, the backlog moves fast and working solutions reach people fast. On the broader AI enablement side, you prototype and test before recommending — enough hands-on work to make confident calls about what actually belongs where. Across both, you are accountable for outcomes. Deployed tools that go unused are not counted as wins. WHAT ARE YOU ACCOUNTABLE FOR PROCESS ANALYSIS AND OPPORTUNITY IDENTIFICATION You map how work actually flows across the agency — where time is spent, where handoffs break down, where decisions stall, and where the same effort repeats. You bring process mining discipline to this analysis: decomposing workflows into their component steps, quantifying the cost of each, and identifying precisely where AI intervention creates the most leverage. This analysis feeds both the automation backlog and the broader AI evaluation pipeline. WORKFLOW AUTOMATION VIA N8N From the process analysis, you identify and prioritise the workflows best suited for automation. You score opportunities by recoverable time and implementation effort, brief the implementation team to build in n8n, and sign off before anything reaches the people using it. The backlog is always live and prioritised. The team always has clear direction. BROADER AI USE CASE IDENTIFICATION AND RECOMMENDATION You are continuously scanning for AI opportunities that fall outside the automation backlog — the knowledge management problems, the information retrieval gaps, the workflow friction that structured tooling could solve without a custom build. You prototype and test candidate solutions hands-on before recommending them, and you own the recommendation. Examples: evaluating whether call transcripts belong in NotebookLM or a structured database; deciding how client information should be stored and surfaced to the working group; assessing whether a shared Claude Project or a purpose-built integration better serves a team's needs. TOOL EVALUATION AND SELECTION When a new need surfaces — from a team conversation, a champion observation, or your own analysis — you evaluate the right tool to address it. That means picking up the candidate tools, running them against real agency content and workflows, and forming a considered view before any recommendation is made. You build enough to know what you are recommending and why. ADOPTION AND OUTCOME TRACKING You track usage and outcomes across everything deployed — automations, knowledge tools, AI-assisted workflows. You measure what is working and what is getting traction, identify friction early, and direct iteration before patterns calcify. The measure of success is the agency operating differently: time recovered, knowledge accessible, decisions faster. WHAT GOOD JUDGEMENT LOOKS LIKE A significant part of this role is making good technology decisions quickly. The agency will surface problems. Your job is to evaluate the solution space, prototype where needed, and recommend the right approach. These examples illustrate the kind of thinking the role requires. A process that looks simple but is not A team reports spending several hours a week on a reporting workflow. Before recommending an automation, you map the full process: every step, every decision point, every handoff. You discover that two of the six steps are genuinely repeatable, two require contextual judgement, and two exist only because of a structural gap in how information is shared upstream. The automation brief covers the two repeatable steps. The structural gap becomes a separate recommendation. The judgement steps are left to the person doing them. That kind of decomposition — separating what can be systematised from what genuinely requires a human — is the core analytical skill this role demands. Call transcripts The agency generates call transcripts regularly. The question is how to store them, search them, and put them to use. You prototype the leading options — NotebookLM as a knowledge base, a structured folder system with AI retrieval, a Claude Project with uploaded sources, direct database storage with tagging — and you form a view based on how each performs against real agency content. You recommend the approach that is most useful for the people who need to access the information, and you own the implementation of that recommendation. Client knowledge and working group access Client-related information is scattered across emails, documents, and people's heads. The question is how to centralise it in a way the working group can actually use. You evaluate whether a shared workspace, a structured Notion setup, a Claude Project, or an AI-enhanced document repository best fits how the team works. You test the leading options against real client content before recommending, and you own the rollout. Automation vs. AI-assisted workflow A team is spending significant time on a repeatable task. You assess whether this is an n8n automation opportunity, a prompt playbook, a Claude Project workflow, or a combination. You make the call based on the nature of the task, the technical overhead of each approach, and the team's actual working patterns. Speed of the right solution matters more than elegance of the perfect one. AI FLUENCY REQUIREMENT This role requires someone with genuine, current fluency across the AI tool landscape — someone who uses these tools daily, has strong opinions about where each one excels, and reaches for the right one instinctively when a new problem surfaces. AI Productivity & Knowledge Claude / Claude Projects NotebookLM Gemini / Gems Google Workspace AI Notion AI ClickUp AI Other platforms as needed Automation & Integration n8n — hands-on capable Webhook & API integrations Conditional logic & branching Google Sheets as a data layer Error handling & monitoring Other platforms as needed CANDIDATE PROFILE Change management experience n8n — workflow building, reviewing, and quality sign-off Genuine working fluency across the current AI tool stack Hands-on tool evaluation — prototypes against real content before recommending Prompt engineering — design and evaluate for specific, production-grade use cases Claude Projects and custom AI workspace configuration and deployment NotebookLM and knowledge synthesis tools Google Workspace AI (Docs, Meet, Gmail AI features) Structured data layers: Google Sheets, Notion API and webhook concepts in automation environments Process mining — decomposes workflows into steps, identifies value loss, quantifies automation opportunity Business operations experience — understands how agency functions actually work, not just how they are described Workflow analysis and process mapping across complex, cross-functional operations Leverage prioritisation — scoring and sequencing opportunities under time pressure Technology selection judgement — matches tool to operational problem based on real testing Brief writing — translates process analysis into tight, actionable implementation specs Outcome accountability — tracks adoption and results, not just delivery Change management — moves resistant teams from scepticism to habitual use High-trust relationship building at every level of seniority Clear written communication — briefs, process maps, recommendations, escalation documents WHAT WE OFFER Hybrid working model: three days in the office (Tuesday to Thursday) A competitive salary with opportunities for growth Private medical care at Medicover Multisport card Annual education budget of $250 Generous employee referral program Catered office lunch every Tuesday Snacks and occasional breakfasts available in the office

Full job record

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Org ID0c2902eb-4c26-44da-aef1-5270415bb825
Source ID9b0564fb-de43-40fa-a0ec-45fe8a64c6db
Board ID9b0564fb-de43-40fa-a0ec-45fe8a64c6db
Providerbamboohr
Provider Job Key363
TitleAI Transformation and Enablement Manager
Normalized Title
Statusactive
Activeyes
Location TextWarsaw, Mazowieckie, 01-211, Poland
Department
Team
Employment Typecontract
Workplace Typehybrid
Remote Policyhybrid
Country
RegionMazowieckie
CityWarsaw
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://delveaccount.bamboohr.com/careers/363
Apply URLhttps://delveaccount.bamboohr.com/careers/363
First Seen At2026-05-30 05:59:01Z
Last Seen At2026-06-06 10:23:20Z
Last Checked At2026-06-06 10:23:20Z
Last Changed At2026-05-30 05:59:01Z
Inactive At
Source Posted At2026-03-24 00:00:00Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=bamboohr/board=delveaccount/date=2026-06-06/2026-06-06T10-23-18-950Z-d50a39eb3f8ecd2d71992153691a4aa6d47fc2a252e01c1db086dac4560412ae.json
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    "description": "<p><span style=\"color: rgb(0, 180, 166); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">WHO WE ARE</span></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 10pt\">Delve Deeper is a performance media agency focused on the charity and nonprofit sector, partnering with organizations that invest $5M–$20M annually in media. We help mission-driven teams maximize impact through advanced digital strategies that drive measurable, scalable results.</span></p>\n<p><br><span style=\"font-family: arial, helvetica, sans-serif; font-size: 10pt\">Our expertise includes advanced analytics, intent-based audience segmentation, full-service media management, and personalized creative—delivering a fully integrated, data-driven approach to growth.</span></p>\n<p><br><span style=\"font-family: arial, helvetica, sans-serif; font-size: 10pt\">More than a vendor, we serve as a strategic partner, helping organizations solve complex media challenges and turn them into clear outcomes. With decades of leadership experience, Delve Deeper is a trusted voice in the charity space.</span></p>\n<p><br><span style=\"font-family: arial, helvetica, sans-serif; font-size: 10pt\">We’ve also been named Built In Colorado’s “Best Places to Work” for five consecutive years, reflecting a culture that values performance, growth, and people. As a privately owned company, we move quickly, support our team holistically, and create meaningful opportunities for advancement.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(0, 180, 166); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">ROLE OVERVIEW</span></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 10pt\">You are accountable for making AI work across the agency — in practice, at scale, producing results people can feel. The foundation of this role is a rigorous understanding of how the business actually operates: where time goes, how decisions get made, where information stalls, and which processes are ripe for change.</span> <br><br></p>\n<p><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">This role has two connected areas of ownership. The first is fast, iterative workflow automation: mapping processes analytically, identifying where the agency is losing time, and getting working solutions built and adopted quickly via n8n. The second is broader AI enablement: identifying where the right AI tool — applied to the right operational problem — can change how the agency stores knowledge, surfaces information, or supports decisions.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">Both areas start from the same place: a clear-eyed read of how work actually flows. This person brings business operations experience and process mining skills to that analysis — the ability to observe a workflow, decompose it analytically, identify where value is being lost, and design the right intervention. AI is the toolkit. Business acumen is what determines where to point it.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">Speed and judgement are the twin engines of the role. On the automation side, the backlog moves fast and working solutions reach people fast. On the broader AI enablement side, you prototype and test before recommending — enough hands-on work to make confident calls about what actually belongs where. Across both, you are accountable for outcomes. Deployed tools that go unused are not counted as wins.</span><br></p>\n<p><br></p>\n<p><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\"><span style=\"color: rgb(0, 180, 166); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">WHAT ARE YOU ACCOUNTABLE FOR</span></span><br><br></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">PROCESS ANALYSIS AND OPPORTUNITY IDENTIFICATION</span></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 10pt\">You map how work actually flows across the agency — where time is spent, where handoffs break down, where decisions stall, and where the same effort repeats. You bring process mining discipline to this analysis: decomposing workflows into their component steps, quantifying the cost of each, and identifying precisely where AI intervention creates the most leverage. This analysis feeds both the automation backlog and the broader AI evaluation pipeline.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">WORKFLOW AUTOMATION VIA N8N</span></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 10pt\">From the process analysis, you identify and prioritise the workflows best suited for automation. You score opportunities by recoverable time and implementation effort, brief the implementation team to build in n8n, and sign off before anything reaches the people using it. The backlog is always live and prioritised. The team always has clear direction.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">BROADER AI USE CASE IDENTIFICATION AND RECOMMENDATION</span></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 10pt\">You are continuously scanning for AI opportunities that fall outside the automation backlog — the knowledge management problems, the information retrieval gaps, the workflow friction that structured tooling could solve without a custom build. You prototype and test candidate solutions hands-on before recommending them, and you own the recommendation. Examples: evaluating whether call transcripts belong in NotebookLM or a structured database; deciding how client information should be stored and surfaced to the working group; assessing whether a shared Claude Project or a purpose-built integration better serves a team's needs.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">TOOL EVALUATION AND SELECTION</span></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 10pt\">When a new need surfaces — from a team conversation, a champion observation, or your own analysis — you evaluate the right tool to address it. That means picking up the candidate tools, running them against real agency content and workflows, and forming a considered view before any recommendation is made. You build enough to know what you are recommending and why.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">ADOPTION AND OUTCOME TRACKING</span></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 10pt\">You track usage and outcomes across everything deployed — automations, knowledge tools, AI-assisted workflows. You measure what is working and what is getting traction, identify friction early, and direct iteration before patterns calcify. The measure of success is the agency operating differently: time recovered, knowledge accessible, decisions faster.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\"><span style=\"color: rgb(0, 180, 166); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">WHAT GOOD JUDGEMENT LOOKS LIKE</span></span></p>\n<p><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">A significant part of this role is making good technology decisions quickly. The agency will surface problems. Your job is to evaluate the solution space, prototype where needed, and recommend the right approach. These examples illustrate the kind of thinking the role requires.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(27, 42, 74); font-family: Arial, sans-serif; font-size: 10pt; font-weight: bold\">A process that looks simple but is not</span></p>\n<p><span style=\"color: rgb(68, 68, 96); font-family: Arial, sans-serif; font-size: 10pt\">A team reports spending several hours a week on a reporting workflow. Before recommending an automation, you map the full process: every step, every decision point, every handoff. You discover that two of the six steps are genuinely repeatable, two require contextual judgement, and two exist only because of a structural gap in how information is shared upstream. The automation brief covers the two repeatable steps. The structural gap becomes a separate recommendation. The judgement steps are left to the person doing them. That kind of decomposition — separating what can be systematised from what genuinely requires a human — is the core analytical skill this role demands.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(27, 42, 74); font-family: Arial, sans-serif; font-size: 10pt; font-weight: bold\">Call transcripts</span></p>\n<p><span style=\"color: rgb(68, 68, 96); font-family: Arial, sans-serif; font-size: 10pt\">The agency generates call transcripts regularly. The question is how to store them, search them, and put them to use. You prototype the leading options — NotebookLM as a knowledge base, a structured folder system with AI retrieval, a Claude Project with uploaded sources, direct database storage with tagging — and you form a view based on how each performs against real agency content. You recommend the approach that is most useful for the people who need to access the information, and you own the implementation of that recommendation.</span><br></p>\n<p><br></p>\n<p><span style=\"color: rgb(27, 42, 74); font-family: Arial, sans-serif; font-size: 10pt; font-weight: bold\">Client knowledge and working group access</span></p>\n<p><span style=\"color: rgb(68, 68, 96); font-family: Arial, sans-serif; font-size: 10pt\">Client-related information is scattered across emails, documents, and people's heads. The question is how to centralise it in a way the working group can actually use. You evaluate whether a shared workspace, a structured Notion setup, a Claude Project, or an AI-enhanced document repository best fits how the team works. You test the leading options against real client content before recommending, and you own the rollout.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(27, 42, 74); font-family: Arial, sans-serif; font-size: 10pt; font-weight: bold\">Automation vs. AI-assisted workflow</span></p>\n<p><span style=\"color: rgb(68, 68, 96); font-family: Arial, sans-serif; font-size: 10pt\">A team is spending significant time on a repeatable task. You assess whether this is an n8n automation opportunity, a prompt playbook, a Claude Project workflow, or a combination. You make the call based on the nature of the task, the technical overhead of each approach, and the team's actual working patterns. Speed of the right solution matters more than elegance of the perfect one.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(68, 68, 96); font-family: Arial, sans-serif; font-size: 10pt\"><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\"><span style=\"color: rgb(0, 180, 166); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">AI FLUENCY REQUIREMENT</span></span></span></p>\n<p><span style=\"color: rgb(43, 74, 82); font-family: Arial, sans-serif; font-size: 10pt; font-style: italic\">This role requires someone with genuine, current fluency across the AI tool landscape — someone who uses these tools daily, has strong opinions about where each one excels, and reaches for the right one instinctively when a new problem surfaces.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">AI Productivity &amp; Knowledge</span></p>\n<ul>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Claude / Claude Projects</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">NotebookLM</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Gemini / Gems</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Google Workspace AI</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Notion AI</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">ClickUp AI</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Other platforms as needed</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\"><span style=\"font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">Automation &amp; Integration</span></span></p>\n<ul>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">n8n — hands-on capable</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Webhook &amp; API integrations</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Conditional logic &amp; branching</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Google Sheets as a data layer</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Error handling &amp; monitoring</span></li>\n<li><span style=\"color: rgb(0, 0, 0); font-family: Arial, sans-serif; font-size: 8pt\">Other platforms as needed</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"color: rgb(0, 180, 166); font-family: Arial, sans-serif; font-size: 8pt; font-weight: bold\">CANDIDATE PROFILE</span></p>\n<ul>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt; font-weight: bold\">Change management experience</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">n8n — workflow building, reviewing, and quality sign-off</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">Genuine working fluency across the current AI tool stack</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">Hands-on tool evaluation — prototypes against real content before recommending</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">Prompt engineering — design and evaluate for specific, production-grade use cases</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">Claude Projects and custom AI workspace configuration and deployment</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">NotebookLM and knowledge synthesis tools</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">Google Workspace AI (Docs, Meet, Gmail AI features)</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">Structured data layers: Google Sheets, Notion</span></li>\n<li><span style=\"color: rgb(26, 26, 46); font-family: Arial, sans-serif; font-size: 10pt\">API and webhook concepts in automation environments</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Process mining — decomposes workflows into steps, identifies value loss, quantifies automation opportunity</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Business operations experience — understands how agency functions actually work, not just how they are described</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Workflow analysis and process mapping across complex, cross-functional operations</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Leverage prioritisation — scoring and sequencing opportunities under time pressure</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Technology selection judgement — matches tool to operational problem based on real testing</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Brief writing — translates process analysis into tight, actionable implementation specs</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Outcome accountability — tracks adoption and results, not just delivery</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Change management — moves resistant teams from scepticism to habitual use</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">High-trust relationship building at every level of seniority</span></li>\n<li><span style=\"font-family: Arial, sans-serif; font-size: 10pt\">Clear written communication — briefs, process maps, recommendations, escalation documents</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"color: rgb(68, 68, 68); font-size: 10pt\"><span style=\"color: rgb(0, 180, 166); font-size: 8pt; font-weight: bold\">WHAT WE OFFER</span></span><br></p>\n<ul>\n<li><span style=\"font-size: 10pt\">Hybrid working model: three days in the office (Tuesday to Thursday)</span></li>\n<li><span style=\"font-size: 10pt\">A competitive salary with opportunities for growth</span></li>\n<li><span style=\"font-size: 10pt\">Private medical care at Medicover</span></li>\n<li><span style=\"font-size: 10pt\">Multisport card</span></li>\n<li><span style=\"font-size: 10pt\">Annual education budget of $250</span></li>\n<li><span style=\"font-size: 10pt\">Generous employee referral program</span></li>\n<li><span style=\"font-size: 10pt\">Catered office lunch every Tuesday</span></li>\n<li><span style=\"font-size: 10pt\">Snacks and occasional breakfasts available in the office</span></li>\n</ul>",
    "compensation": null,
    "departmentId": null,
    "locationType": "2",
    "seekPromoted": false,
    "jobCategoryId": null,
    "jobOpeningName": "AI Transformation and Enablement Manager",
    "departmentLabel": "",
    "jobOpeningStatus": "Open",
    "minimumExperience": null,
    "jobOpeningShareUrl": "https://delveaccount.bamboohr.com/careers/363",
    "employmentStatusLabel": "Contractor"
  }
}
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GET https://api.bluedoor.sh/job-postings/v1/jobs/c14392abaa5151b1def81f5ad7fb20b63efdfc07?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/0c2902eb-4c26-44da-aef1-5270415bb825JSON
GET https://api.bluedoor.sh/job-postings/v1/sources/9b0564fb-de43-40fa-a0ec-45fe8a64c6dbJSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/c14392abaa5151b1def81f5ad7fb20b63efdfc07/eventsJSON