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Generative AI Engineer
GuestWorld. Identify opportunities and develop generative AI and machine learning use cases in collaboration with business teams .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and implementing AI/ML solutions, with a strong focus on generative AI, scalable architectures, and data modeling. Proven ability to collaborate with multidisciplinary teams while promoting best practices in technology and continuous improvement.
Highest-signal resume keywords
AI/ML Solution DevelopmentGenerative AI ProjectsPython ProgrammingMachine Learning FrameworksCloud AI/ML Services
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI/ML Solution DevelopmentGenerative AIData PreparationData ModelingSQLPrompt EngineeringModel EvaluationScalable FrameworksAutomationContinuous Improvement
Soft Skills
Analytical MindsetCritical ThinkingStrong CommunicationStakeholder ManagementCollaborative Mindset
Tools & Technologies
TensorFlowPyTorchScikit-learnMLflowAzureGitAgile MethodologiesCI/CD Practices
Industry Keywords
AI GovernanceEthicsBias MitigationModel ExplainabilityRAG Architectures
Tech Stack
Tools & technologiesAzureCloudPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- Identify opportunities and develop generative AI and machine learning use cases in collaboration with business teams
- Design, develop, test, and implement AI/ML solutions, from functional and technical specifications through to production deployment
- Contribute to defining and evolving AI solution architectures
- Develop scalable, modular, and reusable components, services, and frameworks
- Prepare, transform, and model data, ensuring the reliability, quality, and contextualization of information
- Collaborate with multidisciplinary teams to implement and evolve solutions
- Promote knowledge sharing and the adoption of technology best practices
- Identify opportunities to improve code, architecture, and development processes
- Contribute to automation, efficiency, and continuous improvement
Requirements
What you’ll need- At least 3 years of experience developing AI/ML solutions, including generative AI projects
- Experience designing solutions, defining architectures, and developing scalable, reusable frameworks
- Knowledge of LLMs, including prompt engineering, RAG architectures, and model evaluation
- Experience with Python and machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, and MLflow), as well as data preparation, data modeling, and SQL
- Knowledge of cloud AI/ML services (preferably Azure), Git, Agile methodologies, and CI/CD practices
- Knowledge of AI governance, ethics, bias mitigation, and model explainability (XAI)
- Analytical mindset, critical thinking, autonomy, initiative, and results orientation
- Strong communication and stakeholder management skills, with a collaborative mindset and ability to work effectively in multidisciplinary teams
- Strong planning and organizational skills, sense of responsibility, and commitment to quality and continuous improvement
Benefits
Comp & perks- Competitive salary and benefits package
- Ongoing training and specialized certifications
- Opportunities for professional growth and development
- Dynamic and collaborative work environment