If you are a senior AI and software engineering professional with a strong background in designing and delivering production-grade AI systems, we invite you to join Accenture's fast-growing Artificial Intelligence Platform and work as part of a worldwide team of experts. In this role, you will shape the architecture of advanced AI solutions across multiple client engagements, working closely with delivery teams, product stakeholders, and business leaders. You will define end-to-end scalable, reliable and cost-efficient AI architectures, contribute to technical solutioning in business development initiatives and help evolve our platform's AI engineering practices.
Our future colleague will do
Define end-to-end scalable, resilient and efficient architectures for advanced AI systems (including data pipelines, model training and serving, retrieval systems, monitoring, and governance) in multi-stakeholder environments, balancing client needs, technical constraints, timelines, and costs;
Collaborate closely with delivery teams to translate architectural designs into work items and identify and resolve architectural challenges during project execution;
Own or contribute to technical solutioning in business development initiatives, including proposal input, architecture design, and effort estimation;
Mentor senior engineers and contribute to raising architectural and engineering maturity across teams;
Pilot and evaluate emerging tools and AI technologies.
What will help you succeed
Strong experience designing and delivering production-grade AI software systems across different domains;
Proven expertise in designing and/or implementing generative AI systems in production, including agentic systems, RAG pipelines, tool-use patterns, and model adaptation strategies (e.g., fine-tuning of open-source LLMs or diffusion models);
Practical experience in retrieval and knowledge systems, e.g., Vector DBs (Pinecone, Chroma, etc.), ingestion frameworks (Kafka, Debezium, etc.), Graph DBs (AWS Neptune, Neo4j);
Breadth of knowledge across modern AI technologies, including generative models, deep learning, and predictive ML;
Solid knowledge of cloud-based AI platforms, infrastructure concepts, and MLOps practices, including containerization, orchestrated and/or serverless deployment, monitoring, versioning and governance;
Strong client-facing communication skills, with the ability to reason clearly about trade-offs involving performance, cost, risk, and maintainability;
Collaborative mindset and mentorship-oriented approach to technical leadership.
What we expect
6+ years of professional software engineering experience, including work on distributed, large-scale systems;
3+ years of hands-on experience in data science and machine learning projects delivered into production;
Affinity for multi-layered AI system design in various contexts and use cases (e.g., end-to-end AI systems, Agentic platforms, workflow engines, etc.);
Experience using cloud-based AI platforms (e.g., Azure ML, AWS SageMaker, or equivalent);
Working knowledge of MLOps methodologies, including CI/CD, monitoring, and governance;
Proven progression from hands-on implementation to system-level architectural responsibility.
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Skills Required
- 6+ years professional software engineering experience including distributed, large-scale systems
- 3+ years hands-on experience in data science and machine learning projects delivered into production
- Experience designing and delivering production-grade AI software systems across domains
- Proven expertise designing/implementing generative AI systems in production, including agentic systems, RAG pipelines, tool-use patterns, and model adaptation strategies (e.g., fine-tuning open-source LLMs or diffusion models)
- Practical experience with retrieval and knowledge systems, including Vector DBs (Pinecone, Chroma), ingestion frameworks (Kafka, Debezium), and Graph DBs (AWS Neptune, Neo4j)
- Breadth of knowledge across generative models, deep learning, and predictive ML
- Experience using cloud-based AI platforms (e.g., Azure ML, AWS SageMaker or equivalent)
- Solid knowledge of MLOps practices including CI/CD, containerization, orchestrated/serverless deployment, monitoring, versioning and governance
- Strong client-facing communication skills and ability to reason about trade-offs (performance, cost, risk, maintainability)
- Proven progression from hands-on implementation to system-level architectural responsibility; mentorship and leadership experience
Accenture Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Accenture and has not been reviewed or approved by Accenture.
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Healthcare Strength — Pay is considered competitive when paired with robust insurance options and other perks that compare well with large consulting and IT services peers. Multiple national medical plan options plus dental and vision are positioned as a core strength of the overall package.
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Retirement Support — Retirement support is positioned as a standout feature through a 401(k) dollar-for-dollar match up to a set percentage after eligibility. The package is reinforced by additional financial programs such as savings tools and related resources.
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Parental & Family Support — Parental and caregiving supports are presented as a meaningful benefit differentiator through substantial paid parental leave and multiple caregiver-oriented programs. Backup care and fertility/adoption/surrogacy navigation and reimbursements add breadth to family support beyond leave alone.
Accenture Insights
What We Do
Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services—all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 500,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com.
