Senior AI Engineer

We are looking for a Senior AI Engineer profile, with solid experience building AI solutions in cloud environments and the ability to take them from idea to production.

The ideal person must have a combination of knowledge in software engineering, machine learning, generative AI, data engineering, and cloud. We are looking for someone capable of developing, integrating, deploying, and operating real AI solutions in enterprise environments.

• Demonstrable experience building Artificial Intelligence, Machine Learning, Deep Learning, or Generative AI solutions.
• Hands-on experience developing solutions based on LLMs, RAG, intelligent agents, conversational assistants, copilots, NLP, document classification, information extraction, or computer vision.
• Solid 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, compute, storage, integration, and observability services.
• Experience with relational and non-relational databases, SQL, APIs, and data processing.
• Experience in the design and implementation of data pipelines, batch processes, ETL/ELT, or architectures oriented toward information exploitation.
• 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 necessary to productize AI solutions.
• Knowledge of best practices for security, privacy, data governance, and responsible AI use.
• Ability to work with multidisciplinary teams and communicate with technical, business, and client profiles.
• Autonomy, proactivity, continuous learning capacity, and delivery orientation.
• Fluent in Spanish and English.

• Advanced experience in one of the main cloud ecosystems:
• Azure: Azure OpenAI, AI Search, Azure ML, Databricks, Synapse, Fabric, Functions, AKS, Key Vault, Monitor.
• Google Cloud Platform: Vertex AI, BigQuery, Cloud Run, Cloud Functions, GKE, Pub/Sub, Dataflow, Looker Studio.
• AWS: Bedrock, SageMaker, OpenSearch, Lambda, ECS/EKS, Glue, Redshift, Textract, Comprehend.
• Experience in advanced RAG architectures: chunking, embeddings, vector stores, reranking, hybrid search, relevance evaluation, groundedness, and traceability.
• Experience in designing and implementing agents with tools, memory, planning, API calls, and flow 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 with Terraform, Bicep, CloudFormation, CDK, or similar tools.
• Experience with GPU acceleration, optimized inference, quantization, fine-tuning, model serving, or open source models.
• Experience in evaluating GenAI models and systems: response quality, hallucinations, security, bias, latency, cost, and observability.
• Knowledge of security applied to AI, including OWASP Top 10, OWASP LLM Top 10, DAST, vulnerability validation, or application hardening.
• Experience in data platform modernization, legacy system migration, 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.

What is it like to work at Deloitte?

🤩 High-impact projects where you will have a long career and learning path

☯️ Hybrid-flexible 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

⚽ Good atmosphere inside and outside the office: you will enjoy several team-building activities per year, cultural and sports activities... and much more!

🧘♀️ Comprehensive well-being: take care of yourself with our physical, mental, and financial health program... and with a medical team in the offices!

🤲 Social impact: You can sign up for a large number of national and international volunteering opportunities and pro-bono projects to put your time and talent at the service of those who need it most

🗣️Feedback and continuous learning culture: you will grow in an inclusive environment where equal opportunities and your personalized training plan will boost your development. Can you already see yourself at the Deloitte University in Paris?

🤝 Exclusive benefits for being part of Deloitte: you will be able to enjoy a wide catalog of benefits and a comprehensive flexible compensation plan

Imagine yourself participating in the transformation of the 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 participate in the design, construction, integration, and industrialization of advanced Artificial Intelligence, Machine Learning, and Generative AI solutions for enterprise clients.

Your day-to-day will be highly oriented towards technical execution: building real solutions, taking AI models and systems into production, integrating AI capabilities into business applications, and working with multidisciplinary teams to solve complex problems through technology.

You will be part of projects where it will be necessary to understand the business challenge, select the appropriate technical approach, develop AI components, integrate them with cloud platforms, and ensure that the solution is scalable, secure, observable, and maintainable.

We are looking for a senior, technical, and hands-on person, with the ability to build robust AI solutions and take them to production.

We especially value profiles that

• 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 developments.
• Are capable of transforming a business use case into a viable technical solution.
• Understand the difference between a demo, a proof of concept, an MVP, and an enterprise productive solution.
• Are rigorous with the quality, security, traceability, observability, cost, and maintenance of solutions.
• Know how to work with uncertainty, propose alternatives, and make justified technical decisions.
• Have good communication skills and are capable of explaining complex AI concepts clearly.
• Can act as a technical reference for other team members.
• Maintain a continuous learning attitude in a constantly evolving field.

The goal of the role is to bring in a person capable of building, integrating, and industrializing end-to-end AI solutions, working with modern cloud technologies and actively participating in the entire solution lifecycle.

• Design, develop, and implement Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI solutions applied to 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 participate 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 based on the client context and the solution.
• Implement solutions with cloud AI, data, and application services, such as:
• Azure OpenAI, Azure AI Search, Azure Machine Learning, Azure Databricks, Microsoft Fabric, or Azure Functions.
• Vertex AI, BigQuery, Cloud Run, Cloud Functions, GKE, or Google Cloud data and AI services.
• 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 foundational models, open source models, and managed AI services according to quality, cost, latency, security, privacy, and maintainability criteria.
• Industrialize solutions through MLOps, LLMOps, and DevOps practices, including deployment automation, version control, CI/CD, testing, monitoring, and production operation.
• Develop APIs, microservices, workers, batch pipelines, or serverless components necessary 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 best practices for security, data governance, privacy, and responsible AI use.
• Participate in technical reviews, standard definition, estimations, documentation, project tracking, and team support during delivery.
• Communicate technical decisions, risks, dependencies, and progress clearly to both technical and non-technical profiles.