Gen AI / ML Senior Engineer (AWS, Snowflake, Databricks)

- Design, develop, and deploy Generative AI applications using AWS Bedrock, SageMaker, and open-source LLMs. - Create and optimize prompting strategies, system prompts, guardrails, and evaluation frameworks for LLM applications. - Build RAG pipelines using Bedrock Knowledge Bases, vector stores, or external solutions. - Fine-tune foundation models using SageMaker or Databricks MLflow. - Work with structured and unstructured data (text, documents, logs) to support GenAI use cases. - Implement ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment. - Integrate ML/LLM services with backend systems, APIs, Snowflake data products, and Databricks workflows. - Build CI/CD pipelines for ML/GenAI workloads. - Monitor model performance, detect data/model drift, and automate retraining. - Collaborate with product owners, cloud engineers, data engineers, and architects to translate business requirements into GenAI solutions. - Participate in client workshops, POVs/POCs, and design sessions for new AI/ML use cases. - Produce architecture diagrams, technical documentation, and best-practice guidelines. - Apply responsible AI principles in all solutions, ensuring secure data handling and compliance with enterprise standards. - Explore and benchmark emerging LLMs, embeddings models, and vector database solutions across AWS, Snowflake, and Databricks ecosystems. - Share knowledge, mentor team members, and contribute to internal accelerators or reusable components. Flexible: The work location for this role may include a mix of working remotely, onsite at a client, or in an Accenture office—depending on specific project circumstances. With all our roles, there is some in-person time for collaboration, learning, and building relationships with clients, peers, leaders, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.