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 remote-first position for engineers based in Europe, Turkey, Georgia, Armenia, or the United Arab Emirates with a required overlap of US working hours (2-6 PM CET).
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.
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.
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.
Azure Cloud Services: Hands-on experience with Azure Functions, Azure Storage, 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.
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.
Start Date: ASAP
Location: Remote (99%); must be able to travel freely within Europe for workshops.
Onsite Requirements: Mandatory planning sessions/workshops (2 times a year).
US Time Zone Overlap: Required (2 PM - 6 PM CET)
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