about 3 hours ago
Responsibilities
- Drive complex AI engineering workstreams across multiple business areas.
- Define AI engineering approaches that align with business goals and integration requirements.
- Translate stakeholder needs into structured implementation plans and solution recommendations.
- Guide the implementation of AI-enabled applications and workflow components.
- Establish best practices for prompt orchestration and API integration.
- Design reusable implementation patterns for various AI use cases.
- Contribute to delivery planning and quality standards across AI engineering engagements.
- Mentor and support team members through feedback and guidance.
- Review deliverables for clarity, quality, and business usefulness.
- Collaborate with cross-functional teams to align AI solutions with business needs.
Requirements
- Advanced English proficiency.
- Strong experience in AI application development using Python, SQL, PowerShell, and REST APIs.
- Hands-on experience with Microsoft Azure and its AI services.
- Experience designing LLM-enabled and agentic applications.
- Strong knowledge of AI solution integration and cloud-native architectures.
- Experience with Databricks, Apache Spark, and PySpark.
- Proficient with Git, GitHub, and Azure DevOps.
Benefits
- Flexibility with remote and hybrid work options.
- Career advancement opportunities with international mobility.
- Access to cutting-edge tools and professional development programs.
- Medical, dental, and vision insurance for you and your family.