ml engineer for GenAI solutions

Accenture is a global professional services company that helps businesses, governments, and other organizations build digital cores, optimize operations, accelerate revenue growth, and enhance citizen services. Its AI&Data team delivers data and analytics support, from strategy definition through solution implementation and development, using technologies from partners such as Microsoft, AWS, Google, Oracle, and Snowflake.

• Design and develop GenAI-powered solutions supporting business processes and decision-making across various functional areas;
• Collaborate with business stakeholders, architects, and engineers to identify practical GenAI use cases and translate them into scalable solutions;
• Build and integrate applications leveraging LLMs with cloud AI services such as Snowflake Cortex and AWS Bedrock;
• Design and implement retrieval-augmented generation (RAG/GraphRAG) pipelines combining enterprise data with GenAI models;
• Work with structured and unstructured data, preparing and optimizing pipelines for GenAI use cases;
• Contribute to high-level solution design and hands-on implementation, ensuring solutions are scalable, secure, and maintainable;
• Experiment with prompt engineering, context engineering, agentic orchestration, embeddings, and model configurations to improve solution quality;
• Support POC/POV initiatives by validating GenAI technologies and identifying their business value;
• Collaborate with data engineering teams to integrate GenAI solutions into modern data platforms;
• Stay up to date with evolving GenAI trends and contribute to internal knowledge sharing and capability building.

• Experience with Python and the ability to build data/AI applications;
• Understanding of GenAI/LLM concepts, including context engineering, prompt engineering, embeddings, and RAG;
• Familiarity with Snowflake or other modern data platforms, or willingness to develop in this area;
• Experience with at least one cloud platform: AWS, Azure, or GCP;
• Experience working with APIs and integrating external AI services into applications;
• Understanding of data engineering fundamentals, including data pipelines, data transformation, and working with large datasets;
• Ability to combine architectural thinking with hands-on implementation;
• Strong problem-solving skills and ability to work in a team environment;
• Interest in building production-ready solutions, not only experiments or prototypes;
• Excellent command of spoken and written English (B2 level);
• Nice to have: experience with LangChain, LlamaIndex or similar frameworks, familiarity with vector databases and semantic search solutions, exposure to Snowflake Cortex or similar platform-native GenAI capabilities, experience building RAG-based solutions or LLM integrations, knowledge of MLOps/LLMOps practices, experience with DBT, Airflow or other data pipeline solutions, familiarity with Docker, Kubernetes, and Terraform, basic understanding of AI governance, security, and responsible AI practices, experience working in Agile delivery models.

• Work on projects for international clients;
• Continuous learning through workshops and skill-building initiatives;
• Access to training in soft skills, technical skills, and languages;
• Access to e-learning platforms, GenAI training, and possible co-financing of courses and certifications;
• Individual support from a People Lead and a defined professional development path;
• Possibility of a session with a Coach;
• Employee Assistance Program with legal, financial, and psychological consultations;
• Employee Share Purchase Plan with quarterly dividends for employees who own company shares;
• Paid employee referral program;
• Private medical care and life insurance;
• Access to the Worksmile benefits platform, including the Multisport card.