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Listed on Accenture’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role involves designing end-to-end architectures for production AI systems across multiple client engagements, balancing technical, cost, and business requirements. It suits senior AI engineers with hands-on experience in generative AI and MLOps who want to move into architectural leadership while mentoring teams and shaping platform practices.
Our summary, not Accenture’s wording. The full posting is on their site.
Skills this role names
- Apache Kafka
- AWS SageMaker
- CI/CD
- Cloud Platforms
- Containerization
- Data Pipelines
- Deep Learning
- Fine-tuning
- Generative AI
- Graph Databases
- Machine Learning
- MLOps
- Retrieval-Augmented Generation
- Vector Databases
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What they ask for
Required
- 6+ years professional software engineering experience including distributed systems
- 3+ years production machine learning and data science projects
- Experience designing and implementing generative AI systems in production
- Knowledge of vector databases and retrieval systems
- Cloud-based AI platform experience (Azure ML, AWS SageMaker, or equivalent)
- MLOps knowledge including CI/CD, monitoring, and governance
- Strong client-facing communication skills
Nice to have
- Experience with agentic systems and tool-use patterns
- Knowledge of graph databases like Neo4j or AWS Neptune
- Familiarity with ingestion frameworks like Kafka or Debezium
- Experience with model adaptation strategies and fine-tuning open-source LLMs
- Breadth across generative models, deep learning, and predictive ML