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Job Description
Structured overview of role & requirementsAbout This Role
Design, implement, and maintain custom large language model agents and AI-driven analytics tools, including building semantic layers and RAG pipelines.
Create and optimize production-grade data pipelines that provide clean, structured data for ML models and vector databases, with deployment to cloud infrastructure and AI application monitoring.
Evaluate and optimize AI retrieval systems for accuracy and latency, including prompt strategies, embedding models, vector search parameters, and SQL-based validation of AI responses, while collaborating cross-functionally and aligning engineering practices.
Minimum Requirements
Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent experience).
4+ years of experience in data engineering, software engineering, or machine learning engineering, including at least 1 year hands-on AI experience.
Proven experience with orchestration frameworks, vector databases, and modern databases such as Snowflake and SQL Server.
Strong SQL skills and familiarity with cloud platforms (AWS) and CI/CD tools (GitHub Actions).
Ideal Candidate Profile
Experienced in developing AI-driven analytics within production environments, including semantic layers and RAG pipeline construction.
Skilled in building and optimizing data pipelines feeding ML systems with expertise in data modelling and working with cloud infrastructure.
Capable of cross-functional collaboration translating complex business requirements into technical AI features and aligning engineering standards across teams.