Senior Engineer (LLM/Agentic AI)

Requirements

• Degree in Computer Science, Engineering, or related field (or equivalent practical experience).
• At least 2 years of working experience in LLM and Agentic AI workflows .
• Has some experience working on data ingestion pipelines for RAG .
• Experience on building agentic workflows is a plus.
• Has proficiency in Python, with 1 year of hands-on exposure with AWS AI Services.
• Experience working in agile environments with CI/CD pipelines on AWS.
• This role will need to secure a clearance, due to the sensitivity of the project.
• To apply:
• Please send your latest CV in MS Word format to jennifer@zenithinfotech.com.sg
• Appreciate the interest of all applicants; however only shortlisted candidates will be notified.

Additional Information

Zenith Infotech (S) Pte Ltd. was started in 1997, primarily with the vision of offering state-of-the-art IT Professionals and solutions to various organizations and thereby helping them increase their productivity and competitiveness. From deployment of one person to formation of whole IT teams, Zenith Infotech has helped clients with their staff augmentation needs. Zenith offers opportunity to be engaged in long term projects with large IT savvy companies, Consulting organizations, System Integrators, Government, and MNCs. EA Licence No: 20S0237 Job: AI & Data Engineering Role: - Design and maintain scalable, secure and efficient data ingestion pipelines on AWS by collaborating with business stakeholders. - Design and maintain vector stores, embedding pipelines, and RAG architecture on AWS for AI-powered applications. - Write and maintain clean, reusable and well-documented code for agentic workflows using AWS-native services and serverless architecture. - Develop and maintain AI evaluation metrics and guardrails on AWS deployment. - Conduct thorough testing, including unit, integration, and end-to-end testing, to ensure correctness and reliability. - Apply strong algorithmic expertise to optimise and evaluate data processing, retrieval, and inference workflows, ensuring high performance and accuracy in AI systems. - Ensure compliance with data governance, security standards, and regulatory requirements. - Participate in agile development cycles, including sprint planning, daily stand-ups, and retrospectives.

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