Senior AI Engineer

Our client, a leader in data-driven solutions, is seeking Senior AI Engineer to contribute to their AI-driven innovation projects in the US. This role is part of a larger company’s strategy leveraging Generative AI (GenAI) to enhance workflows, decision-making, and data management of the enterprise solutions in tax, auditing and risk management used by the largest companies in the world.

This is a long-term remote-first contract position with a required overlap of US working hours (2-6 PM CET).

Role & Responsibilities

As a Senior AI Engineer, you will:

• Develop and maintain scalable back-end services using FastAPI and other modern frameworks.

• Ensure seamless integration with front-end applications and external services through well-designed RESTful APIs.

• Leverage cloud infrastructure (Azure Functions, Azure Storage) for hosting and scaling applications.

• Implement security best practices for API authentication (OAuth, JWT) and data protection.

• Work on GenAI-driven applications, utilizing frameworks such as LangChain, LlamaIndex, vector databases, and agentic frameworks.

• Containerize applications using Docker for environment management.

Work Conditions

• Type: Full-time & Long-term contract work

• Start Date: ASAP

• Location: Remote (99%) in Europe; must be able to travel freely within Europe for workshops.

• US Time Zone Overlap: Required (2 PM - 6 PM CET)

• Contract with European LLC

• Expertise in Python for back-end development.

• Experience with FastAPI, Pandas, and NumPy for building scalable RESTful APIs.

• Experience with Retrieval Augmented Generation (RAG).

• Proficiency in Prompt Engineering.

• Experience with MCP/FastMCP

• Knowledge of vector databases and embedding models.

• Familiarity with frameworks such as LangChain, LangGraph, and LlamaIndex.

• Ability to work with large datasets and perform data cleaning, transformation, and manipulation.

• Cloud Services: Hands-on experience with AWS/Azure/GCP and cloud-based hosting.

• Asynchronous Programming: Understanding of async patterns to improve performance.

• Containerization: Familiarity with Docker for application deployment.

• Security Best Practices: Knowledge of API authentication methods such as OAuth and JWT.

• Ability to participate in the discussions and lead the technical discussions

• Have a consultancy mindset → always try to find a solution for the client

• Make decisions about the solution and design

Preferred Experience

• Knowledge of AI ethics, bias mitigation, and responsible AI practices.

• Experience with multi-agent libraries/frameworks like CrewAI, Autogen, and Taskweave.

• Understanding data engineering concepts, including data pipelines, data integration, and data warehousing.

• Performance optimization using monitoring tools and profiling techniques.

• Unit testing & automation (PyTest, Unittest).

• CI/CD pipelines for seamless deployment.