AI Engineer
Indexed description
The successful candidate will collaborate with cross-functional engineering teams to build scalable AI capabilities, deploy production-ready solutions, and continuously improve performance, reliability, and governance across AI implementations.
Key Responsibilities
- Design, configure, and integrate AI services such as large language models, computer vision, speech, and language processing capabilities using major cloud platforms.
- Develop, refine, and evaluate prompts to improve the quality, accuracy, and effectiveness of Generative AI applications.
- Prepare, validate, and optimize datasets to support AI model performance and cloud AI services.
- Deploy, monitor, and maintain AI-powered solutions using cloud-native technologies and deployment tools.
- Work closely with solution architects, platform engineers, and cross-functional teams to deliver scalable AI solutions.
- Create and maintain technical documentation, including solution designs, configurations, implementation details, and operational procedures.
- Investigate, troubleshoot, and resolve issues affecting AI applications and cloud-based services.
- Contribute to continuous improvement by adopting AI engineering best practices and sharing technical knowledge within the team.
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related discipline. Equivalent professional experience may also be considered.
- Cloud AI certifications are advantageous but not required.
- 2–5 years of experience in software development.
- At least 1 year of experience integrating cloud-based APIs or AI services.
- Hands-on experience developing applications using Python and RESTful APIs.
- Familiarity with at least one major cloud platform such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
- Cloud-based AI services across Microsoft Azure, AWS, and Google Cloud Platform.
- Generative AI technologies, including prompt engineering and prompt optimization techniques.
- AI service integration using REST APIs and cloud-native architectures.
- Data preparation, preprocessing, and validation for AI applications.
- API integration patterns and application design principles.
- Fundamental cloud security, governance, and compliance concepts.
- AI solution deployment, monitoring, and operational support within cloud environments.
- Strong collaboration skills with the ability to work effectively across engineering, architecture, and business teams.
- Analytical problem-solving skills with the ability to translate business requirements into practical AI solutions.
- Excellent written and verbal communication skills, including the ability to document technical solutions clearly.
- Commitment to continuous learning and keeping current with emerging AI technologies and cloud platform capabilities.
- Strong ownership mindset with a focus on delivering reliable, high-quality AI solutions and operational excellence.
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