AI Engineer – Temporary Contract
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Job Description
AI Engineer building production LLM applications for Applaudo’s AI-powered migration platform. Developing bidirectional sync logic, SQL safeguards, and automated failure-resolution rules.
Responsibilities:
- Prepare context for each migration process, including functional documentation, source schema, and target data model, so the LLM generates accurate mappings in both directions
- Design and tune prompts for proposing queries, mappings, and transformation rules, reducing rework during human review
- Review generated SQL and mappings against both data models, validating entities, fields, relationships, and constraints
- Resolve unreliable LLM cases, including identifiers that change format between systems and data conflicting with constraints while preserving those constraints
- Build parameterized queries to detect changes on each side since the last sync, including non-database sources such as spreadsheets and document folders
- Work with the Senior Python Developer on safeguards for LLM-generated SQL and controlled, approved writes to source systems
- Automatically classify failed-to-sync records by root cause, including conflicts where the same data changed on both sides, and turn treatments into approved rules
- Automate migration preparation tasks such as loading inputs, generating artifacts, and comparing artifact versions
- Version approved artifacts with their source inputs and document preparation procedures for reuse by other teams
Requirements:
- Bachelor's Degree in Computer Science, Engineering, Information Systems, or a related field is desired, or equivalent professional experience
- 3+ years of software development experience with Python and software engineering best practices
- Advanced SQL skills working with PostgreSQL, MySQL, and cloud data warehouses such as BigQuery
- 1+ year of experience building LLM applications that run in production, beyond prototypes
- Experience integrating hosted LLM APIs into production environments, including structured output and its validation
- Experience with prompt engineering, prompt versioning, fallback strategies, and cost and latency optimization
- Experience evaluating LLM output with test cases and clear evaluation methodologies
- Demonstrated ability to understand and modify a partially documented codebase that you did not write
- Demonstrated use of AI tools in your daily workflow, with an explicit step to verify what they produce
- Strong autonomy, attention to detail, and comfort with ambiguity as requirements evolve
- Advanced English fluency
- Experience in data migration or ETL projects
- Experience with Vertex AI or Gemini
- Experience extracting data from spreadsheets or documents
- Experience with MLOps practices, including CI/CD, observability, and reproducible pipelines
Benefits:
- Employees can work remotely
- 2-month contractor framework, with the possibility of extension
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