Senior Full Stack Engineer – AEM

Anchora – Content Practice

We build AEM with AI in the loop from the first line of the ticket to the last line of the release note. This is not a role for someone who is open to trying AI tools - it is for someone who already works this way, delivers more because of it, & can pull an experienced team up to the same level. You will own AEM builds end-to-end, frontend to backend, headless to hosted, for clients who expect senior judgement rather than a pair of hands. If you want a role where your opinion on architecture actually shapes the outcome, keep reading.

The Non-Negotiable: You Already Work AI-First

This is the part of the role we will not compromise on. Anchora sells AI, Data, MarTech & Content work - we cannot credibly sell AI-accelerated delivery to our clients if our own engineers still build the old way. Every engineer we hire from here works AI-first, & at senior level you are expected to set the standard rather than follow it.

• Agentic tooling is your default - you use Claude, Claude Code, GitHub Copilot, Cursor or an equivalent every day, as your primary way of working - not as occasional autocomplete.
• First draft is generated, final draft is yours - you expect code, tests, documentation & analysis to start as AI output, & you own the review that makes it production-grade.
• You know how to set an agent up to succeed - repository context & rules files, reusable prompts & skills, MCP servers, sub-agents, & a plan agreed before the build starts.
• You use AI well beyond code - solution notes, test plans, release notes, data mapping, migration scripts, legacy code comprehension, ticket breakdown, & client-facing summaries.
• You can prove the difference - you can point to specific work where AI changed the outcome - & to work where you deliberately chose not to use it.
• You can teach it - part of this role is lifting the AI maturity of the engineers around you, in code review, in pairing, & in the standards you help write.

If you have not yet worked this way, this is not the role for you - & we would rather say that here than at interview.

Tech Stack at a Glance

• AI Toolchain: Claude & Claude Code, GitHub Copilot, Cursor or equivalent; agentic workflows, MCP servers, project context & rules files, reusable prompt & skill libraries
• AI in the Product: Schema.org structured data, llms.txt & Generative Engine Optimisation (GEO), AEM Content Hub AI capabilities & Generative Variations
• Content Platform: AEM Sites, AEM Assets & Content Hub, AEM Headless (Content Fragments, GraphQL), Adobe Edge Delivery Services
• Backend: Java, Spring, OSGi, Sling, JCR, REST APIs
• Frontend: React JS (or equivalent), HTL/Sightly, modern component architecture
• Platform & Infrastructure: AEM as a Cloud Service (AEMaaCS), Edge Delivery Services, Cloud Manager, Dispatcher, CDN
• Quality Engineering: Playwright, Cypress, Selenium, security & penetration testing
• MarTech Integration: Adobe Analytics, CRM platforms, Schema.org structured data
• Ways of Working: Agile, Scrum ceremonies, AI-accelerated development (Claude, GitHub Copilot)

About Anchora

Anchora is a boutique Adobe-specialist & MarTech & AI consultancy, delivering Adobe Experience Manager (AEM), Data, & Digital Experience engagements for clients across financial services, government, tourism, retail, & beverages. Our Content Practice covers AEM Sites, AEM Assets & Content Hub, AEM Forms, & Edge Delivery Services (EDS), & we pride ourselves on senior, hands-on delivery rather than layered bench teams.

Role Overview

We are looking for a senior full stack engineer who can move confidently across the AEM stack - from component-level frontend work through to backend integration & cloud release - & take genuine ownership of delivery outcomes, with AI amplifying every part of it. You will work directly with architects & client stakeholders across the full lifecycle: design, build, test, & go-live. This is a hands-on role for someone who wants to build, not just advise.

Is This You?

• You have shipped AEM builds that clients still talk about – for the right reasons
• Your working day already starts with an agent & a plan, & you would find it slow to go back
• You have strong opinions about how AI coding tools should be used well – not just that they should
• You would rather flag a risk on day one than explain it in a retro
• You can hold a technical conversation with an architect & a business conversation with a client in the same afternoon
• You are the person on your current team other engineers ask "how did you do that so fast?"

Key Responsibilities

• Deliver every stage of your work AI-first - analysis, design, code, tests, documentation, release notes - using agentic tooling as the default & your engineering judgement as the quality gate
• Set up & maintain the context that makes AI effective on client codebases: repository context & rules files, reusable prompts & skills, MCP integrations, & sub-agent patterns for repetitive work
• Apply AI to the unglamorous work where it pays most - legacy code comprehension, content & data migration scripts, test generation, regression triage, & documentation debt
• Review AI-generated output with the same rigour as human code; you are accountable for what you ship regardless of what wrote it
• Design & build AEM Sites components, templates, & Sling Models across authoring & delivery tiers
• Configure & extend AEM Assets & Content Hub, including Digital Asset Management (DAM) workflows & metadata schemas
• Develop & maintain backend services in Java, integrating AEM with downstream CRM & other enterprise systems
• Build modern, componentised frontend experiences using React JS or an equivalent framework, applying design system & accessibility (WCAG 2.1 AA) standards consistently
• Deliver AEM Headless solutions using Content Fragments & GraphQL, & structure content with Schema.org markup to support search & AI discoverability
• Implement & govern Adobe Analytics integration, including data layer design & tracking accuracy
• Own delivery performance end-to-end - Dispatcher & CDN caching strategy, cache invalidation, page weight, & Core Web Vitals measured against agreed budgets
• Operate & deploy within AEM as a Cloud Service (AEMaaCS), including Cloud Manager pipelines, Dispatcher configuration, & cloud-native release practices
• Work to strong version control discipline - branching strategy, small reviewable pull requests, & meaningful code review of both human & AI-generated changes
• Design & maintain automated test suites using Playwright, Cypress, or Selenium to protect release quality
• Support security testing & penetration (PEN) testing cycles, & remediate findings within agreed timeframes
• Own features end-to-end – from technical design through build, testing, deployment, & hypercare
• Engage directly with client stakeholders in a consulting capacity, translating business requirements into sound technical solutions
• Participate fully in Agile ceremonies – sprint planning, daily stand-ups, retrospectives, & showcases – & contribute to continuous improvement of team practices
• Mentor engineers & contribute to Anchora's AEM delivery standards, reusable patterns, & AI playbooks

Required Skills & Experience

• AI-First Delivery (the primary filter): Demonstrable, current, daily use of AI & agentic coding tools (Claude / Claude Code, GitHub Copilot, Cursor or equivalent) across code, tests, documentation & analysis; ability to structure context, rules & reusable prompts for a real codebase; sound judgement on where AI helps & where it must not be trusted. You will be asked for specific examples in your application & to work this way in a live exercise.
• Experience: 6–8+ years in full stack software engineering, with at least 4 years dedicated to Adobe Experience Manager (AEM)
• AEM Platform Engineering: AEM Sites component & template development across frontend & backend – Sling Models, HTL/Sightly, client libraries, OSGi services, workflow models, & JCR content modelling
• Assets, Content Hub & Headless: AEM Assets & Content Hub, including Digital Asset Management (DAM) workflows & metadata governance; AEM Headless via Content Fragments & GraphQL; structured content modelling with Schema.org markup for search & AI discoverability
• Backend & Integration: Strong core Java (Java 8+), Spring, & RESTful API design; integration with backend CRM platforms such as Salesforce or Dynamics, & with Adobe Analytics for data layer implementation & tracking
• Frontend, Design Systems & Accessibility: React JS or an equivalent modern frontend framework (Angular, Vue); component-based design systems with documentation & governance; Web Content Accessibility Guidelines (WCAG) 2.1 AA standards applied consistently
• Cloud, Hosting & Infrastructure: AEM as a Cloud Service (AEMaaCS), including Cloud Manager pipelines, Dispatcher configuration, CDN, DNS, & environment topology across non-production & production tiers
• Quality & Security Engineering: Test automation with Playwright, Cypress, or Selenium for end-to-end & regression coverage; working knowledge of security testing & exposure to penetration (PEN) testing, including remediation
• Delivery, Agile & AI-Accelerated Development: End-to-end delivery ownership within Agile teams, including active participation in Scrum ceremonies; practical use of AI coding assistants such as Claude & GitHub Copilot to accelerate development with sound judgement
• Consulting, Communication & Certification: Client-facing consulting or agency experience; excellent written & verbal communication with both technical & non-technical stakeholders; at least one current Adobe Certification (e.g. AEM Sites Developer, AEM Developer, or equivalent)

Nice to Have

• AI Tooling You Have Built: Custom agents, MCP servers, skills, evals, or internal automations you have built for your own team - this is the strongest possible signal for this role
• Edge Delivery Services: Familiarity with Adobe Edge Delivery Services (EDS) as an alternative authoring model
• AEM Forms: Experience with AEM Forms, including adaptive forms & submission integration
• Multi-Site & Localisation: Multi Site Manager (MSM), Live Copy, & translation or localisation workflows across markets
• Node JS & Microservices: Building services & tooling with Node.js; microservices architecture & inter-service integration patterns
• Adobe Experience Platform Suite: Exposure to Adobe Target, Adobe Journey Optimizer (AJO), Customer Journey Analytics (CJA), or similar Adobe Experience Platform applications
• Adobe Workfront & Creative Cloud: Workfront for work management & creative operations; Creative Cloud applications & asset production workflows
• Other CMS Platforms: Experience with other content management systems such as Sitecore, Drupal, or headless CMS platforms (e.g. Contentful, Contentstack)
• Salesforce: Salesforce Commerce Cloud for eCommerce integrations, or Salesforce CRM configuration, customisation or administration

How We Use AI - & Where We Draw the Line

Being AI-first is not the same as being uncritical. We hold a high bar on how AI is used, & we expect you to hold it with us.

• AI writes the first draft; you own the last one - you are accountable for everything you ship, regardless of what generated it.
• If you cannot explain it, you cannot commit it - code you cannot defend in review or debug under pressure does not go in.
• Client data & code go only where they are allowed to go - every engagement runs under Anchora's AI Usage Policy & the client's own AI terms, which set the approved tools & conditions for that project. No shortcuts, no personal accounts, no exceptions.
• Throughput at quality, not volume - AI that produces more code & more defects is a net loss. We measure outcomes, not lines.
• The tooling moves monthly - we expect you to keep up, form your own view, & bring what works back to the team.

What Success Looks Like

• AI Leverage: You consistently deliver more, at higher quality, than this role would have produced two years ago - & the team can see exactly how, because you have shown them
• Client Handling: Clients see you as a trusted technical partner, not just an executor – you ask the right questions before you build, & you flag risk early rather than at the retro
• Project Delivery: Sprint commitments are met consistently; when something slips, you communicate it before it becomes a surprise, with a plan already attached
• Proactive Communication: Status updates go out before they're asked for; blockers are raised the day they appear, not the day before the deadline
• Attitude: You bring energy to hard problems, take ownership without being asked twice, & make the people around you better – in code review, in stand-up, & under pressure
• Technical Craft: Your code, tests & documentation are something the next engineer is glad to inherit - & something an agent can work in without breaking

Don't Tick Every Box? Apply Anyway

We would rather hear from someone with the right attitude & a genuine appetite to learn than lose a great engineer over a skills checklist. If you meet most of the Must Have requirements & can show us how you learn & upskill quickly, we want your application. The one requirement we do not flex on is AI-first working - everything else is negotiable.

Culture Fit

Technical skill gets you shortlisted; culture fit gets you hired. We are looking for someone who takes ownership, communicates proactively, & genuinely enjoys working closely with clients & teammates – culture fit is assessed as a core requirement alongside technical capability, not an afterthought.

How to Apply

Please submit your CV along with a cover letter via this portal. Your application must:

• Address the Requirements - we want to see in your cover letter & CV how you meet each of the requirements outlined above. If you don't meet it exactly but think you have transferrable skills, explain what they are. 
• Include a Cover Letter - applicants that do not submit a customised cover letter for this role will not be considered. The cover letter should include:
  • How you actually work with AI - be specific. Which tools, on what kind of work, what you have changed about how you use them over the last six months, & one example where AI clearly changed the outcome of a piece of work.
  • Why you are the right fit - including anything that does not come through in a CV - how you learn new technology, examples of teamwork or stakeholder interactions, or moments where your attitude made the difference on a project.

Applications that do not address these points will not progress.

Our Hiring Process

1. If you pass our screening requirements, which include checking the points above & answering the screening questions in the application portal, we will arrange an Initial Interview with the hiring manager.
2. If proceeding to the next stage, you will be sent a Technical Test to do in your own time. This is an
   AI-assisted technical exercise. You will use your own tooling - we are not interested in whether you can code with the tools switched off.
3. If you pass the Technical Test you will proceed to a Technical Interview with a tech lead on the team to review your your Technical Test, ask you questions about it, and potentially undertake a live debug+fixes exercise.
4. If proceeding to the next stage, you will undertake a Final Interview with other interviewers to check cultural fit & ask any final questions.
5. If proceeding, we will make a Verbal Offer & agree on employment terms.
6. We will then Check your References & complete a background check.
7. A formal employment offer & Contract will be signed by both parties if you pass your reference & background check.