Custom Software Engineer
About the job
- A minimum of 5 years of AEM development experience in production environments.
- A minimum of 1 year of hands-on AI-assisted development in a production AEM delivery context, demonstrable through specific examples.
- A bachelor's degree in computer science, computer engineering, software engineering, or a related field.
- A 15-year full-time education background.
- Deep proficiency in Adobe Experience Manager Sites, including component development, content modelling, MSM, DAM integration, and workflow design.
- Hands-on expertise with HTL (Sightly), Sling Models, OSGi/Felix, and Java in production-grade delivery.
- Working experience with Cloud Manager CI/CD pipelines, content versioning, and cloud-native OSGi development patterns.
- Working knowledge of EDS block development, Franklin/Helix authoring, and performance-first web delivery principles.
- Experience setting team-level AI standards and proficient use of GitHub Copilot and Claude for code generation, architecture assistance, test authoring, and AEM documentation.
- Understanding of orchestration frameworks including LangGraph, LangChain, and CrewAI, as well as RAG pipelines and how AEM content APIs connect to agent-based architectures.
- Strong proficiency in Java, JavaScript, HTL (Sightly), and Python.
- Knowledge of Adobe platform developer APIs including AEM, Firefly, AEP, and AJO.
- Experience with Kubernetes, Docker, microservices, and CI/CD pipelines.
- Experience leading Agile teams and running sprint ceremonies with workstream-level delivery accountability.
- Demonstrated team lead or senior individual contributor experience with delivery accountability alongside hands-on technical contribution.
- Experience with Adobe Experience Manager Sites is required.
- Lead client requirement sessions, use artificial intelligence to synthesize briefs, surface gaps, and draft technical specifications, then validate solution proposals.
- Act as a subject-matter expert and build complex components using Sling Models, OSGi, HTL, and Java, using artificial intelligence to accelerate pattern-based development while fully reviewing generated output.
- Define the team's testing strategy, implement generated test suites and automated quality gates, and maintain a shared library of AEM-specific prompts for component generation, OSGi configuration, and code review.
- Develop AEM integrations with third-party APIs, DAM, and CRM systems, and diagnose and resolve complex performance issues using AI-assisted observability tooling.
- Govern Cloud Manager pipelines, manage Oak indexes and dispatcher configuration, and implement cloud-native OSGi patterns.
- Guide the team on Edge Delivery Services block development and Helix/Franklin authoring, using artificial intelligence to accelerate block scaffolding and performance analysis.
- Integrate LLM APIs with AEM-adjacent application layers, manage token limits, latency, and cost trade-offs, and apply prompt versioning, AI output observability, and cost monitoring across the team's AI toolchain.
- Lead and coordinate the AEM team, own sprint velocity, quality, and delivery milestones, and mentor junior engineers on AEM best practices and AI-native habits.
- Define team-level standards for AI-assisted development, including prompt libraries, code-review workflows for generated code, and quality gates.
- Lead technical design sessions, architecture walkthroughs, and code-with sessions with client engineering teams, communicating trade-offs and AI tool limitations.
- Analyze requirements, propose solutions, help design architecture, and write production-grade AEM code.
- Set and model AI-native engineering standards from requirement analysis through deployment and observability.
- Participate in technical design sessions, mentor junior AEM engineers, embed directly with client engineering teams, and build reusable AI-accelerated AEM patterns.
About the company
Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.
Company Size
10,001+
Company Stage
IPO
Headquarters
Dublin, Ireland
Founded
1989
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Simplify's Take
What believers are saying
- Business demand grew: October 2026 results showed $74.2 billion annual revenue, up 5% in local currency.
- Eligible US employees buy discounted stock: Accenture's purchase plan sells shares at 15% below market price.
- Client relationships run deep: Accenture has worked with 195 of its top 200 customers for more than ten years.
What critics are saying
- Bookings are not guaranteed revenue: most Accenture contracts let clients cancel quickly with little or no penalty.
- Promotions require AI adoption: Accenture's CEO said in March 2026 that employees must use its tools effectively.
- Federal hiring practices proved costly: Accenture settled discrimination allegations for $25 million in September 2026, without a liability finding.
What makes Accenture unique
- Its AI platform switches models: AI Refinery selects among prebuilt models according to cost, performance and other requirements.
- Accenture owns specialist Microsoft expertise: it cofounded the Microsoft-focused Avanade consultancy with the software maker.
- Consulting includes creative agencies: Accenture Song owns businesses spanning advertising, digital product design and customer engagement.
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Benefits
Health Insurance
Professional Development Budget
401(k) Retirement Plan
401(k) Company Match
Company News
Accenture will hold an Investor Day on October 14, where it is expected to detail its long-term strategy, AI monetisation plans, growth guidance, and margin expansion goals. The event follows a rebound in its shares after fears that AI would erode traditional consulting work. The stock hit a low of $118.15 in June, down from a January high of $291.09. It has since gained nearly 77%, helped by fourth-quarter results on October 1 and an expanded collaboration with Dell Technologies. Fourth-quarter revenue rose 6% to $18.7 billion, and new bookings reached $22.2 billion. Accenture expects fiscal 2027 revenue growth of 3% to 6% in local currency. It raised its quarterly dividend by 5% to $1.71 per share, payable November 13, 2026. Its market capitalisation is about $139.6 billion.
Accenture has acquired Sagacity, a London-based data and customer intelligence firm, to strengthen Accenture Song's AI-powered customer services. The deal brings more than 140 professionals to Accenture Song's UK and Ireland operations. Terms were not disclosed. Founded in 2005 by Anita Dougall, Malka Townshend, and Harry Dougall, Sagacity offers data assets, AI-enabled technology, and customer intelligence expertise. Accenture says clients want to connect data, AI, and operations into unified programmes that deliver measurable results. The move targets industries with large customer bases, such as utilities, retail, banking, and telecommunications. "Sagacity's deep expertise and outcome-focused approach will enhance our ability to help clients turn insight into action," said Sohel Aziz, senior managing director of Accenture Song, UK and Ireland.
TM Forum has launched a multi-year Trustworthy AI programme with Accenture to help telecoms deploy autonomous operations with verifiable trust standards. The initiative will deliver the industry's first Trustworthy AI Governance Certification, providing a benchmark for trusted AI deployment. Recent TM Forum research found that whilst 72% of communications service providers believe their AI capabilities are trustworthy, only 14% can verify their claims. The programme aims to transform AI trust from aspiration into measurable operational capability. The certification will help organisations assess governance maturity, workforce readiness, and operational accountability needed to scale AI autonomously. It will operate through TM Forum's AI-Native Collaboration Studios, where telecoms operators, vendors, and partners will contribute real-world use cases to shape the framework.
Accenture reported revenue of nearly $74.2 billion for fiscal year 2026, up 6.5% year-over-year, with net income of roughly $8.5 billion. The professional services firm serves approximately 9,000 clients globally with 814,000 employees. Microsoft generated revenue of nearly $331.8 billion in FY 2026, a 17.8% increase, with net income of approximately $133.7 billion. The company's net margin reached close to 40.3%. Both companies maintained a debt-to-equity ratio of approximately 0.3x. Microsoft's free cash flow reached nearly $67.0 billion, whilst Accenture's was roughly $11.6 billion. Accenture recently addressed a $25 million settlement with the Department of Justice regarding federal contracting practices. Microsoft faces securities fraud class action lawsuits involving AI and Copilot claims, alongside antitrust scrutiny and an IRS tax audit.
Accenture shares surged 17% on Thursday after reporting strong fourth-quarter results. The company posted revenue of $18.7 billion, up 6% year-over-year, while earnings per share jumped 46% to $3.29. Management's full-year revenue growth forecast of 4.5% exceeded analyst expectations of 4%. Net bookings rose 4% to $22.2 billion. The company plans to return at least $9.5 billion to shareholders this financial year. However, TD Cowen analyst Bryan Bergin maintained a hold rating, citing concerns that the stock is fully priced at 15 times forward earnings. He cautioned that one strong quarter may represent a cyclical bounce rather than structural growth acceleration. Despite this, Wall Street remains optimistic, with a "moderate buy" consensus rating. Accenture currently offers a 3.05% dividend yield.