AI Engineer

Overview

Essential duties & responsibilities:

• Requirement Analysis: Collaborate with business stakeholders to gather requirements and define solution objectives aligned with business goals.
• Development and Implementation: Lead solution implementation including data integration, model development, and deployment. Engineer and improve AI systems and tools. Build prototypes, POCs, and MVPs to bring solutions in a structured manner.
• Platform: Support the AI platform implementation, ensuring robustness and reliability.
• Security and Compliance: Ensure AI solutions adhere to security best practices and data privacy regulations.
• Documentation and Training: Create technical documentation and best practice guidelines. Provide training on AI technologies.
• Monitoring and Maintenance: Implement monitoring to track AI solution performance and proactively address issues.
• Architecture: Design scalable, secure, and compliant AI solutions in collaboration with AI architects, integrating smoothly with existing IT infrastructure.
• Development and Implementation: Develop, test, and implement solutions following SDLC best practices, including version control, code review, and CI/CD processes.
• Quality Assurance and Testing: Execute comprehensive testing strategies and resolve defects.
• Integration and System Connectivity: Manage AI solution integration with internal and external systems, ensuring data consistency and interoperability.
• Documentation and Change Management: Produce detailed documentation for AI processes and handle changes with minimal disruption. Contribute to best practice development.
• Stakeholder Engagement and Communication: Facilitate effective communication between technical teams and business stakeholders, managing interactions and escalations.
• Professional Development and Innovation: Stay current with AI trends and encourage team innovation by exploring new tools and techniques.
  

Education & trainings:

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field (Master's degree in Science preferred).
• Fluent spoken and written English. Any other language is a plus.
• Azure certifications such as Azure AI Engineer Associate are a plus.
  

Qualifications & experience:

• Experience in software engineering.
• Experience with AI/ML or data science roles, with a focus on building AI solutions on Azure preferred.
• Proficient in Python or C#, with strong Azure cloud experience.
• Skilled in Azure AI services (Copilot Studio, Cognitive Services, Machine Learning, OpenAI, Search, Blob Storage, Web App, Functions).
• Experience with LLMs, Generative AI, machine learning, NLP, and computer vision models.
• Knowledge of DevOps practices, CI/CD pipelines
• Ability to translate complex business requirements into functional specifications for effective project implementation.
• Experienced in agile environments for timely, quality solution delivery.
  

Physical & mental requirements:

• Ability to work well with cross-functional teams, multi-task and meet deadlines consistently
• Good communication (verbal and written) and interpersonal skills, attention to detail and ability to communicate complicated issues effectively.
• Demonstrated ability to perform consistently under varying business pressure as well as ability to adapt to a quickly changing environment.
• Effective problem-solving skills, ensuring the ability to address challenges promptly and efficiently.