AI engineer for enterprise clients

Can you imagine taking part in the transformation of leading national and international organizations? At Deloitte, we are committed to making an impact on society, our clients, and you. As a Senior AI Engineer, you will take part in designing, building, integrating, and industrializing advanced Artificial Intelligence, Machine Learning, and Generative AI solutions for enterprise clients. Your day-to-day work will be highly focused on technical execution: building real solutions, bringing AI models and systems into production, integrating AI capabilities into business applications, and working with multidisciplinary teams to solve complex problems through technology.

• Design, develop, and implement Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI solutions for real business use cases.
• Build solutions based on LLMs, RAG systems, intelligent agents, conversational assistants, enterprise copilots, document classification, information extraction, NLP, computer vision, or advanced analytics.
• Actively take part in the technical development of AI components, including data ingestion, preprocessing, embeddings, semantic search, prompt orchestration, response evaluation, API integration, and service deployment.
• Work with cloud platforms such as Microsoft Azure, Google Cloud Platform, and AWS, using the most suitable services for the client and solution context.
• Implement solutions using cloud AI, data, and application services, such as Azure OpenAI, Azure AI Search, Azure Machine Learning, Azure Databricks, Microsoft Fabric, or Azure Functions.
• Implement solutions using cloud AI, data, and application services, such as Vertex AI, BigQuery, Cloud Run, Cloud Functions, GKE, or Google Cloud data and AI services.
• Implement solutions using cloud AI, data, and application services, such as Amazon Bedrock, SageMaker, OpenSearch, Lambda, ECS/EKS, Glue, Redshift, or equivalent AWS services.
• Design and implement data pipelines and ETL/ELT processes to feed AI and advanced analytics solutions.
• Train, evaluate, fine-tune, deploy, and monitor Machine Learning and Deep Learning models.
• Evaluate and compare foundation models, open-source models, and managed AI services based on quality, cost, latency, security, privacy, and maintainability.
• Industrialize solutions using MLOps, LLMOps, and DevOps practices, including deployment automation, version control, CI/CD, testing, monitoring, and production operations.
• Develop APIs, microservices, workers, batch pipelines, or serverless components needed to integrate AI capabilities into business applications.
• Collaborate with software engineering, data engineering, architecture, security, product, and business teams to deliver end-to-end solutions.
• Apply good practices in security, data governance, privacy, and responsible AI use.
• Take part in technical reviews, standards definition, estimates, documentation, project tracking, and supporting the team during delivery.
• Clearly communicate technical decisions, risks, dependencies, and progress to both technical and non-technical audiences.

• Demonstrable experience building Artificial Intelligence, Machine Learning, Deep Learning, or Generative AI solutions.
• Practical experience developing solutions based on LLMs, RAG, intelligent agents, conversational assistants, copilots, NLP, document classification, information extraction, or computer vision.
• Strong experience with Python and the AI and data library ecosystem, such as Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Semantic Kernel, or similar frameworks.
• Experience designing and implementing solutions on at least one of the main cloud platforms: Azure, Google Cloud Platform, or AWS.
• Practical knowledge of cloud AI, data, computing, storage, integration, and observability services.
• Experience with relational and non-relational databases, SQL, APIs, and data processing.
• Experience designing and implementing data pipelines, batch processes, ETL/ELT, or architectures focused on information utilization.
• Experience deploying solutions in production, not just developing notebooks or proofs of concept.
• Knowledge of MLOps, LLMOps, DevOps, CI/CD, testing, and monitoring practices.
• Ability to develop backend components, APIs, services, integrations, or automated processes needed to productionize AI solutions.
• Knowledge of good practices in security, privacy, data governance, and responsible AI use.
• Ability to work with multidisciplinary teams and communicate with technical, business, and client audiences.
• Autonomy, proactivity, ability to learn continuously, and delivery orientation.
• Fluent Spanish and English.
• We are looking for a senior, technical, hands-on person who can build robust AI solutions and bring them into production.
• Enjoy developing real solutions, not just defining architectures or prototypes.
• Have the judgment to choose between proprietary models, open-source models, managed services, or custom-built solutions.
• Be able to turn a business use case into a viable technical solution.
• Understand the difference between a demo, a proof of concept, an MVP, and an enterprise production solution.
• Be rigorous about solution quality, security, traceability, observability, cost, and maintenance.
• Know how to work with uncertainty, propose alternatives, and make justified technical decisions.
• Have good communication skills and be able to explain complex AI concepts clearly.
• Be able to act as a technical reference for other team members.
• Maintain a continuous learning mindset in a constantly evolving field.
• Будет плюсом: Advanced experience in one of the main cloud ecosystems: Azure OpenAI, AI Search, Azure ML, Databricks, Synapse, Fabric, Functions, AKS, Key Vault, Monitor; Advanced experience in one of the main cloud ecosystems: Vertex AI, BigQuery, Cloud Run, Cloud Functions, GKE, Pub/Sub, Dataflow, Looker Studio; Advanced experience in one of the main cloud ecosystems: Bedrock, SageMaker, OpenSearch, Lambda, ECS/EKS, Glue, Redshift, Textract, Comprehend; Experience with advanced RAG architectures: chunking, embeddings, vector stores, reranking, hybrid search, relevance evaluation, groundedness, and traceability; Experience designing and implementing agents with tools, memory, planning, API calls, and workflow orchestration; Experience with vector databases or semantic search engines such as Azure AI Search, OpenSearch, Pinecone, Weaviate, Milvus, Chroma, FAISS, or similar; Experience with Docker, Kubernetes, serverless architectures, microservices, or event-driven architectures; Experience with orchestration tools such as Airflow, Prefect, Dagster, or equivalents; Knowledge of infrastructure as code using Terraform, Bicep, CloudFormation, CDK, or similar tools; Experience with GPU acceleration, optimized inference, quantization, fine-tuning, model serving, or open-source models; Experience evaluating GenAI models and systems: response quality, hallucinations, security, bias, latency, cost, and observability; Knowledge of AI security, including OWASP Top 10, OWASP LLM Top 10, DAST, vulnerability validation, or application hardening; Experience modernizing data platforms, migrating legacy systems, or enterprise data modeling; Previous experience in regulated sectors such as banking, healthcare, energy, insurance, industry, or public administration; Cloud or AI certifications in Azure, GCP, AWS, Databricks, or other relevant platforms

• High-impact projects with plenty of room for growth and learning.
• A flexible hybrid day-to-day: you will have flexible hours and a good balance between remote work and teamwork in our offices or those of our clients.
• A good atmosphere inside and outside the office: you will enjoy several team-building events each year, cultural and sports activities, and much more!
• Comprehensive well-being: take care of your physical, mental, and financial health with our program, and with a medical team in the offices!
• Social impact: You can sign up for many volunteering opportunities at national and international levels and pro bono projects where you can put your time and talent at the service of those who need it most.
• A culture of feedback and continuous learning: you will grow in an inclusive environment where equal opportunities and your personalized training plan will support your development. Can you already picture yourself at Deloitte University in Paris?
• Exclusive benefits for being part of Deloitte: you can enjoy a wide range of benefits and a comprehensive flexible compensation plan.