About the Role
As an AI Engineer, you will play a key role in designing, developing, and deploying enterprise Generative AI solutions that drive business innovation and operational efficiency. You will build AI-powered applications, intelligent agents, and Retrieval-Augmented Generation (RAG) solutions while collaborating with cross-functional teams to integrate AI capabilities into enterprise platforms and business processes.
Responsibilities
- Design, develop, and enhance AI-powered applications using Large Language Models (LLMs) and modern AI frameworks.
- Build and maintain Retrieval-Augmented Generation (RAG), Agentic AI, and conversational AI solutions.
- Develop AI orchestration workflows using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, and Model Context Protocol (MCP).
- Integrate enterprise applications with AI services such as Azure OpenAI, OpenAI, Anthropic Claude, and other LLM platforms.
- Design and optimize prompts, AI workflows, and context management to improve response quality, accuracy, and cost efficiency.
- Implement AI guardrails, evaluation frameworks, hallucination mitigation, and responsible AI practices.
- Develop scalable APIs and backend services using Python and FastAPI.
- Participate in solution design, architecture discussions, and technical reviews.
- Collaborate with business stakeholders to identify AI use cases and translate business requirements into technical solutions.
- Support deployment, monitoring, and continuous improvement of AI applications in production environments.
Skills
- Strong programming skills in Python.
- Hands-on experience with Generative AI, Large Language Models (LLMs), and Prompt Engineering.
- Experience building RAG, Agentic AI, and Multi-Agent applications.
- Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar orchestration frameworks.
- Experience integrating AI services such as Azure OpenAI, OpenAI, Anthropic Claude, or equivalent LLM platforms.
- Knowledge of Vector Databases, embeddings, semantic search, and AI evaluation techniques.
- Experience developing REST APIs using FastAPI or similar frameworks.
- Familiarity with Git, Docker, cloud platforms (Azure/AWS), and CI/CD practices.
- Strong analytical, debugging, and problem-solving skills.
- Excellent communication skills with the ability to collaborate across technical and business teams.
Our Interview Practices
To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.
Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.
