AI Infrastructure Architect
About the job
- A minimum of 5 years of software or platform engineering experience, with 5 to 8 years specified in the role profile.
- At least 2 years focused on artificial intelligence, machine learning, or agentic systems.
- Deep expertise in Google Cloud Platform services including Vertex AI, Gemini, Vertex AI Pipelines, Feature Store, Google Kubernetes Engine, and Pub/Sub.
- Production experience building large language model-powered applications with tool use, multi-turn reasoning, and agent memory.
- Proficiency in Python.
- Strong understanding of asynchronous patterns, concurrency, and distributed systems.
- Hands-on experience with agentic frameworks such as Agent Development Kit, LangChain, LangGraph, and CrewAI.
- Experience with vector databases, embedding pipelines, and hybrid search architectures.
- Strong command of Google Cloud Platform security, including Identity and Access Management, Workload Identity, VPC Service Controls, and Secret Manager.
- A track record of delivering high-availability and low-latency services, with Service-Level Objectives and Service-Level Agreement ownership.
- Completion of 15 years of full-time education.
- Architect and build custom artificial intelligence infrastructure and hardware solutions.
- Optimize artificial intelligence infrastructure and hardware performance, power consumption, cost, and computational-stack scalability.
- Advise on artificial intelligence infrastructure technology and vendor evaluation, selection, and full-stack integration.
- Build multi-agent orchestration systems using Vertex AI, Agent Builder, LangGraph, and AutoGen.
- Design scalable and resilient pipelines integrating large language model reasoning, tool calling, memory management, and human-in-the-loop flows.
- Lead the design and implementation of retrieval-augmented generation systems using Vertex AI Search, Matching Engine, and enterprise vector stores.
- Define and enforce Google Cloud Platform infrastructure standards using a security-first approach across Google Kubernetes Engine, Cloud Run, Eventarc, and Apigee.
- Drive machine learning operations practices including model evaluation, agent observability, tracing, logging, and continuous-improvement loops.
- Partner with product, data science, and platform teams to translate business requirements into agentic solutions.
- Conduct in-depth code reviews and architecture reviews.
- Mentor developers with 3 to 5 years of experience.
- Contribute to internal developer platforms, software development kits, and reusable agent components.
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
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Company News
Accenture (NYSE: ACN) is betting on enterprise AI as its main growth engine. At its Investor and Analyst Day, the company targeted at least mid-single-digit constant-currency revenue growth in fiscal 2027 and 2028, rising to mid- to high-single-digit growth from fiscal 2029. Chief executive officer Julie Sweet said AI will create new demand that exceeds work lost to automation. The company has grown its AI and data workforce from 40,000 to nearly 110,000. Accenture plans to return $9.5 billion to shareholders in fiscal 2027 and spend about $5 billion on acquisitions. It expects annual operating-margin growth of 10 to 30 basis points. Its network of specialised businesses, now 6% of revenue, could double by fiscal 2029. Fiscal 2026 revenue was $74.2 billion, up 5% in local currency.
Accenture shares rose 10.4% after the company reported higher sales and earnings for its fourth quarter and full year in early October 2026. It confirmed fiscal 2027 guidance, raised its quarterly dividend to $1.71 per share, and completed a long-running share repurchase program. The company also expanded its AI alliances with Dell and Workday and acquired Sagacity. It aims to embed agentic AI into client functions such as HR, finance, and customer engagement. Accenture's narrative projects $86.3 billion in revenue and $10.3 billion in earnings by 2029, up from $8.4 billion today. Pricing pressure and slower discretionary spending remain the main risks.
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.