Senior AI Engineer

Job Responsibilities and Duties 

• Build AI-assisted solutions for code analysis, system transformation, refactoring, and migration.
• Analyze application architecture, source code, dependencies, data, metadata, and logs.
• Design and integrate generative AI, NLP, retrieval, and other machine learning capabilities into migration workflows.
• Develop reliable pipelines to generate, test, validate, and deploy transformed code and software components.
• Create evaluation methods for functional correctness, regression, performance, security, and maintainability.
• Build cloud-based AI services, APIs, data pipelines, and automation for production use.
• Apply sound software engineering practices, including clean code, testing, documentation, versioning, and traceability.
• Provide technical guidance and mentor engineers while remaining directly involved in design and development.

Qualifications 

• 5–10 years of relevant experience in software engineering, AI, machine learning, or system modernization.
• MSc or PhD in Computer Science, Machine Learning, Software Engineering, or a related field.
• Strong Python programming skills and experience delivering production software.
• Experience with generative AI, NLP, embeddings, retrieval-augmented generation, or related AI methods.
• Experience with PyTorch, TensorFlow, or equivalent machine learning frameworks.
• Strong understanding of software architecture, APIs, dependency management, testing, and system integration.
• Experience working with structured and unstructured data, SQL, and data transformation pipelines.
• Experience with cloud platforms such as Azure, AWS, or Google Cloud, and container technologies such as Docker.
• Ability to explain technical decisions clearly and work effectively in evolving problem spaces.

Additional Qualifications 

• Experience with code intelligence, static analysis, parsers, abstract syntax trees, compilers, or dependency graphs.
• Experience migrating or modernizing applications across languages, frameworks, databases, or cloud environments.
• Experience with MLOps tools, model evaluation, experiment tracking, monitoring, and scalable inference.
• Experience building developer tools or AI-assisted software engineering platforms.
• Experience with enterprise systems in Energy, Insurance, Healthcare, or another regulated industry.