AI Engineer
Posted Updated
- Independently integrate and configure AI services (e.g., LLMs, vision, speech, language APIs) from Azure, AWS, and GCP
- Develop, optimize, and test prompts for LLMs and generative AI
- Prepare, preprocess, and validate data for use with platform AI services
- Deploy and monitor AI-powered solutions using cloud-native tools
- Collaborate with architects and platform engineers to deliver AI solutions
- Document solution configurations, code, and operational procedures
- Troubleshoot and resolve issues in AI solutions
- Education – Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent professional experience)
- Cloud platform certifications (Azure AI Fundamentals, AWS Certified AI Practitioner) are beneficial
- Related Work Experience
- 2-5 years of software development experience
- 1+ year of experience integrating cloud APIs or services
- Experience with Python and REST APIs
- Familiarity with at least one cloud platform (Azure, AWS, or GCP)
- Knowledge
- Comprehensive knowledge of Azure AI services (Azure OpenAI, Cognitive Services, Speech, Vision)
- Comprehensive knowledge of AWS AI services (Bedrock, SageMaker endpoints, Rekognition)
- Comprehensive knowledge of GCP AI services (Vertex AI, Cloud AI APIs)
- Advanced knowledge of prompt engineering techniques and optimization
- Knowledge of data preprocessing and validation
- Understanding of API design and integration patterns
Basic knowledge of cloud security and compliance
Skills –
- Collaboration: Works effectively with architects, platform engineers, and business users
- Problem Solving: Breaks down AI requirements into manageable configurations
- Communication: Clearly documents solutions and technical decisions
- Continuous Learning: Stays current with platform AI capabilities and latest practices