AI Software Engineer

Overview

The AI Software Engineer will develop and deploy AI-driven solutions that enhance data management, governance, and automation activities across organizational workstreams. The role demands building scalable AI applications and services that enable metadata enrichment, data profiling, anomaly detection, duplicate detection, rule recommendation, remediation support, and intelligent automation within a secured sovereign AI environment.

Key Responsibilities

• Design, code, test, and deploy AI-powered applications and microservices supporting enterprise needs.
• Create scalable AI and machine learning solutions automating business and data processes.
• Develop reusable AI frameworks, APIs, and enterprise-wide services.
• Optimize AI models and applications for efficiency, reliability, and scalability.
• Implement AI-driven metadata enrichment to boost data discoverability and governance.
• Build intelligent data profiling to detect patterns, quality issues, and relationships in data.
• Automate classification and tagging for enterprise datasets.
• Develop machine learning models for anomaly detection and data quality monitoring.
• Create duplicate detection and entity matching algorithms to improve data consistency.
• Maintain and improve model accuracy and performance over time.
• Develop AI systems that recommend data quality rules and optimize them.
• Implement engines that assist users in resolving data-related issues.
• Build intelligent remediation workflows and automated corrective processes.
• Develop generative AI solutions including Large Language Models (LLMs) and AI agents to enhance business workflows.
• Utilize prompt engineering, retrieval-augmented generation (RAG), and AI workflow orchestration techniques.
• Integrate generative AI capabilities into existing enterprise platforms.
• Ensure compliance with sovereign AI requirements, including security, privacy, and governance standards.
• Implement monitoring, security controls, and auditing for AI applications.
• Collaborate with architects, data engineers, product owners, and stakeholders to translate business needs into AI solutions.
• Participate in code reviews, testing, deployment, and support to uphold high engineering standards.
• Maintain up-to-date technical documentation and disseminate best practices within the team.

Qualifications and Experience

• Bachelor’s or Master’s degree in Computer Science, AI, Software Engineering, Data Science, or related field.
• Minimum 5 years of software engineering experience, including at least 2 years focused on AI/ML solution development.
• Proven track record of delivering large-scale AI applications in production environments.
• Strong grasp of software development lifecycle, CI/CD, and DevOps methodologies.

Technical Proficiencies

• Programming languages: Python (required), Java, C#, or Node.js.
• Experience with RESTful APIs and microservices architectures.
• Version control and DevOps tools such as Git and CI/CD pipelines.
• Machine learning frameworks: Scikit-learn, TensorFlow, PyTorch.
• Expertise in ML model development, deployment, anomaly detection, and NLP/text analytics.
• Generative AI tools and concepts: Azure OpenAI Service / OpenAI APIs, LLMs, prompt engineering, RAG, AI agents, workflow automation.
• Data technologies: SQL and NoSQL databases, data profiling, quality frameworks, governance, and metadata management tools.
• Familiarity with ETL/ELT processes and data engineering fundamentals.
• Cloud and platform experience, primarily Microsoft Azure, including Azure AI Foundry, Azure Machine Learning, Azure Databricks.
• Containerization technologies like Docker and Kubernetes.

Preferred Qualifications

• Experience in regulated, government, or sovereign cloud environments.
• Knowledge of data governance, data quality, and master data management.
• Relevant certifications like Microsoft Azure AI Engineer Associate (AI-102).
• Understanding and practical implementation of Responsible AI and governance frameworks.

Personal Competencies

• Advanced software engineering and systems design capabilities.
• Strong analytical and problem-solving aptitude.
• Ability to translate complex business requirements into effective AI solutions.
• Excellent communication skills with stakeholders.
• Innovative mindset focused on automation and continual improvement.
• Proven collaboration and teamwork skills.