Accenture Flex offers you the flexibility of local fixed-duration project-based work powered by Accenture, a leading global professional services company. Accenture is consistently recognized on FORTUNE's 100 Best Companies to Work For and Diversity Inc's Top 50 Companies For Diversity lists.

As an Accenture Flex employee, you will apply your skills and experience to help drive business transformation for leading organizations and communities. In addition to delivering innovative solutions for Accenture's clients, you will work with a highly skilled, diverse network of people across Accenture businesses who are using the latest emerging technologies to address today's biggest business challenges.

You will receive competitive rewards and access to benefits programs and world-class learning resources. Accenture Flex employees work in their local metro area onsite at the project, significantly reducing and/or eliminating the demands to travel.

• The AI Agent Data/ML Engineer will design, develop, and operationalize AI agents, largescale data pipelines, and machine learning solutions to support enterprise automation and analytics initiatives.

• This role requires strong engineering skills, expertise in LLM and agentic architectures, and the ability to deploy AI systems securely and reliably within a regulated environment.

• Strong understanding of LLM integration, functioncalling patterns, prompt engineering, and agent orchestration.

• Experience deploying ML models using MLflow, Azure ML, SageMaker, Kubeflow, or similar.

• Proficiency in TensorFlow, PyTorch, Scikit-Learn, or equivalent ML frameworks.

• Experience building scalable data pipelines using Spark, Databricks, or similar technologies.

• Strong knowledge of RAG patterns, vector databases (FAISS, Pinecone, Chroma, Milvus, Redis), and embedding optimization.

• Experience with CI/CD pipelines, automated testing, code reviews, and deployment automation.

• Familiarity with containerization (Docker) and orchestration (Kubernetes).

• Experience integrating AI agents with enterprise APIs, microservices, and workflow systems.

• Familiarity with reasoning models, transformer architectures, and enterprise AI use cases.

• Knowledge of cloud platforms: Azure (preferred), AWS, or GCP.

• Experience with streaming technologies (Kafka, EventHub, Kinesis).

• Understanding of Responsible AI concepts, model fairness, bias detection, and safety filters.

• Experience with highcompliance environments (financial services, healthcare, or government).