Senior AIML Engineer

Colombo - Sri Lanka

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

Design develop and implement Generative AI solutions that address business and analytical use cases
Build scalable API-driven applications integrating Large Language Models using cloud-based services
Apply prompt engineering techniques to optimise LLM performance accuracy and relevance
Implement and manage LLM orchestration frameworks and vector databases to support advanced GenAI workflows
Conduct rapid experimentation and evaluation of new GenAI models tools and capabilities
Develop maintain and optimise data pipelines supporting structured and unstructured data for AI solutions
Collaborate with GenAI leads product owners and cross-functional teams to deliver requirements from the product backlog
Translate complex business problems into robust technical GenAI solutions
Monitor debug and resolve issues across AI models data pipelines and application layers
Leverage cloud platforms such as Azure AWS or GCP for storage compute serverless processing and AI services
Ensure AI solutions meet performance scalability security and reliability standards
Contribute to architecture decisions best practices and continuous improvement initiatives
Document solution designs implementation approaches and operational procedures
Stay current with emerging trends tools and advancements in Generative AI and data engineering

Requirements

3 years of hands-on experience in data analytics data engineering or modern software development roles
Strong background in AI/ML with a focus on Generative AI solutions
Proficiency in programming languages such as Python PySpark or Java
Experience integrating Large Language Models via APIs and building scalable AI-driven systems
Hands-on experience with vector databases and LLM orchestration frameworks
Solid understanding of prompt engineering and model optimisation techniques
Experience building and maintaining data pipelines and ETL processes
Exposure to cloud-native services on Azure AWS or GCP
Bachelors or Masters degree in Computer Science Statistics Mathematics or a related field

Design develop and implement Generative AI solutions that address business and analytical use casesBuild scalable API-driven applications integrating Large Language Models using cloud-based servicesApply prompt engineering techniques to optimise LLM performance accuracy and relevanceImplement and ma...

Design develop and implement Generative AI solutions that address business and analytical use cases
Build scalable API-driven applications integrating Large Language Models using cloud-based services
Apply prompt engineering techniques to optimise LLM performance accuracy and relevance
Implement and manage LLM orchestration frameworks and vector databases to support advanced GenAI workflows
Conduct rapid experimentation and evaluation of new GenAI models tools and capabilities
Develop maintain and optimise data pipelines supporting structured and unstructured data for AI solutions
Collaborate with GenAI leads product owners and cross-functional teams to deliver requirements from the product backlog
Translate complex business problems into robust technical GenAI solutions
Monitor debug and resolve issues across AI models data pipelines and application layers
Leverage cloud platforms such as Azure AWS or GCP for storage compute serverless processing and AI services
Ensure AI solutions meet performance scalability security and reliability standards
Contribute to architecture decisions best practices and continuous improvement initiatives
Document solution designs implementation approaches and operational procedures
Stay current with emerging trends tools and advancements in Generative AI and data engineering

Requirements

3 years of hands-on experience in data analytics data engineering or modern software development roles
Strong background in AI/ML with a focus on Generative AI solutions
Proficiency in programming languages such as Python PySpark or Java
Experience integrating Large Language Models via APIs and building scalable AI-driven systems
Hands-on experience with vector databases and LLM orchestration frameworks
Solid understanding of prompt engineering and model optimisation techniques
Experience building and maintaining data pipelines and ETL processes
Exposure to cloud-native services on Azure AWS or GCP
Bachelors or Masters degree in Computer Science Statistics Mathematics or a related field