Job Description
Job DescriptionWe are looking for an AI Engineer to create practical, employee-facing applications that improve how internal teams find information, complete work, and make decisions. This role partners closely with business stakeholders to uncover operational challenges, shape effective solutions, and deliver reliable tools from concept through production support. The ideal candidate brings strong engineering depth, sound product judgment, and hands-on experience building applied AI systems that drive measurable efficiency and adoption.
Responsibilities:
• Partner with business leaders and end users to map workflows, identify inefficiencies, and define high-value AI solutions for internal operations.
• Design, build, and deploy AI-powered applications in Python using model APIs, orchestration frameworks, and enterprise-ready software practices.
• Develop retrieval-based experiences that enable users to search, analyze, and ask questions across internal documents and structured data sources.
• Create end-to-end automated processes that connect language models with business platforms, data systems, and human review checkpoints where needed.
• Architect agent-driven or multi-step AI solutions with clearly defined roles, secure permissions, and dependable coordination between components.
• Strengthen application quality through thoughtful testing, monitoring, documentation, deployment standards, and ongoing performance improvements.
• Assess model behavior for factual quality, consistency, traceability to source material, and usefulness in real business scenarios.
• Build intuitive user interfaces that allow employees to interact with AI tools easily without requiring technical expertise.
• Manage post-launch ownership by resolving issues, incorporating user feedback, and delivering enhancements that improve reliability and adoption.
• Present technical decisions, tradeoffs, and business impact clearly to both technical teams and non-technical stakeholders.• At least 5 years of experience in software engineering, data engineering, data science, or a closely related discipline.
• Minimum 2 years of hands-on experience developing and deploying applications that use large language models in production settings.
• Demonstrated track record of building AI solutions that have been released to users and supported after launch.
• Strong proficiency in Python and experience working with enterprise platforms, APIs, and application integrations.
• Practical knowledge of retrieval-augmented generation, embeddings, and vector search techniques for knowledge-driven applications.
• Experience creating agent-based systems or multi-stage AI workflows that coordinate model output with business processes.
• Ability to apply sound engineering practices in testing, evaluation, error handling, access control, and long-term application support.
• Bachelor’s degree in computer science, data science, information systems, or a related field.