AI Engineer

Job Qualifications for AI Engineer:

• 3+ years of software engineering, AI engineering, machine learning, data engineering, or related experience
• Strong proficiency in Python.
• Experience building AI-enabled applications using large language models (LLMs).
• Experience working with APIs, cloud services, and application integration.
• Familiarity with retrieval-augmented generation (RAG), semantic search, enterprise search, vector databases, or similar technologies
• Understanding of prompt engineering and grounding techniques.
• Experience processing structured and unstructured content, including documents, spreadsheets, reports, websites, PDFs, and databases.
• Experience designing systems that leverage metadata, search, filtering, and knowledge retrieval.
• Understanding of software development best practices including source control, testing, documentation, and deployment
• Familiarity with SQL and database principles.

Preferred Qualifications:

• Experience with Azure AI, Azure OpenAI, AWS AI services, Claude, OpenAI, or comparable AI platforms.
• Experience developing AI assistants, copilots, chat applications, or intelligent search solutions.
• Familiarity with machine learning workflows and model evaluation techniques
• Experience with document processing, knowledge management, or enterprise search platforms.
• Experience with Power BI, Tableau, or other visualization tools.
• Familiarity with cloud application architecture and secure enterprise environments.
• Experience working with large-scale data integration projects.

Responsibilities for AI Engineer:

• Designing and developing AI-enabled applications and intelligent search solutions.
• Building and maintaining document ingestion, content processing, and knowledge management workflows.
• Implementing retrieval, search, filtering, and ranking capabilities
• Developing prompts, orchestration logic, and response frameworks for AI applications.
• Building metadata models and information structures that improve retrieval quality.
• Configuring AI systems to provide transparent, grounded, and reliable responses.
• Developing integrations between AI services, data repositories, cloud platforms, and business applications.
• Testing and validating AI outputs for quality, consistency, relevance, and usability.
• Troubleshooting retrieval, search, prompt, and performance issues