We Are
Accenture is a global leader in technology consulting, driving innovation across industries with cutting-edge AI and Machine Learning (ML) solutions. Our teams collaborate with clients to develop scalable, practical AI/ML systems that align with business objectives. Our expertise spans multiple industries and leverages partnerships with leading technology providers.
Role Summary
We are seeking a highly skilled Generative AI Engineer with hands-on experience in building, training, tuning, and scaling Generative AI applications. This role requires an individual who specializes in the end-to-end (i.e., full-stack) design and development of agentic solutions. The ideal candidate will have experience in AI and Generative AI frameworks, full-stack development, and a proven ability to tailor models and solutions for real-world deployment.
Responsibilities
Design, develop, and deploy end-to-end Generative AI solutions tailored for specific business needs.
Build, train, and fine-tune large language models (LLMs) and generative models for various applications.
Work with vector databases and generative AI frameworks and libraries to implement agentic architectures.
Collaborate with cross-functional teams to integrate AI models into existing software systems using full-stack development frameworks such as React and Node.js.
Deploy AI models on cloud platforms (AWS, GCP, Azure) ensuring scalability and reliability.
Develop APIs and user interfaces (UX) to make AI capabilities accessible and user-friendly.
Adopt and implement modern data architecture principles (e.g., data mesh, knowledge graphs, and ontologies).
Engage in prompt engineering and model selection to optimize AI performance for specific tasks.
Participate in agile development processes, using tools like Git and Jira to manage workflows and sprints.
Ensure the security and compliance of AI-powered applications through the implementation of appropriate controls.
Professional Skills Requirements:

3+ years of experience in AI/ML development with 1+ years of hands-on experience using Generative AI solutions.
AI / Agentic Architectures: Experience working with vector databases and generative AI frameworks and libraries.
LLM Selection and Training: Expertise in selecting, training, fine-tuning, and prompt engineering large language models (commercial and/or open source).
Python: Proficiency in Python programming language for AI model development and deployment.
Cloud Platforms: 3+ yrs proficiency deploying models on one or more cloud platforms such as AWS, GCP, or Azure.
API / UX Development: Proven hands-on experience with API development and user interface design and development (e.g., using Node.js and React).
Knowledge of modern data architectures (data mesh, knowledge graph, and ontology principles).
Cross-Functional Collaboration: Proven ability to collaborate in cross-functional teams, using tools like Git, Jira, and agile methodologies.
Ability to stay updated with the latest advancements in AI and Generative AI technologies and apply them to practical use cases.
3+ years of Industry Experience in Communications, Media & Technology, OR, Financial Services, OR, Healthcare, OR, Resources, OR, Products.
Preferred (Nice-to-Have) Skills
MLOps Tools and Workflows: Familiarity with MLOps tools and workflows such as MLFlow, Kubeflow, or Airflow.
DevOps Practices: Experience with DevOps practices, including CI/CD pipelines, containerization (e.g., Docker), and orchestration (e.g., Kubernetes).
Security Controls: Experience implementing security controls for AI-powered applications.
Industry-Specific Use Cases: Experience with Generative AI use cases for specific industries such as healthcare, retail, finance, high tech, energy, etc.