Cloud Data Migration & AI Systems Engineer
Type: Long-term contract (9 months)
Location: Remote (India or Brazil)
8 hours per day with an overlap of 8 hours with PST.
Commitment: 40 hours/week, 8 hours PST overlap
Start Date: Immediate
Role Overview
As an Agentic Evaluation Specialist, you will work directly with researchers at a top 8 Frontier large language model company to improve LLM Agent performance specific for Agentic Storage Management.
Responsibilities:
Data migration workflows across cloud platforms (AWS, GCP, Azure)
Data migration strategies, considering trade-offs (online vs offline, performance, scalability)
Creation & upkeep of data pipelines and ETL/ELT workflows in distributed environments
Integrate and evaluate LLM/Generative AI components within workflows
Perform system testing and validation: Execute test scenarios, Identify edge cases and failure points, Debug and analyze issues across systems
Ensure data integrity, consistency, and performance across systems
Document findings, insights, and recommendations clearly for stakeholders
Collaborate with cross-functional teams across engineering, data, and product
Required Qualifications:
5+ years of relevant experience with cloud platforms (GCP, AWS, or Azure) and data/storage systems
Strong understanding of data migration processes and associated trade-offs
Experience with data pipelines, ETL/ELT workflows, or distributed systems
Hands-on exposure to LLMs / Generative AI (prompting, evaluation, or integration)
Experience in system testing, validation, or QA
Strong debugging and problem-solving skills
Excellent written communication skills
Nice to have:
Background in storage administration, SRE, or cloud infrastructure operations
Experience with MLOps, model evaluation frameworks, or AI testing workflows
Familiarity with Google Cloud Storage (GCS) or similar platforms
Experience working in Agile environments with cross-functional teams
Process:
Fill out an interest check form on our client's portal
15-minutes AI Interview
Skills Required
- 5+ years of relevant experience with cloud platforms (GCP, AWS, or Azure) and data/storage systems
- Strong understanding of data migration processes and associated trade-offs
- Experience with data pipelines, ETL/ELT workflows, or distributed systems
- Hands-on exposure to LLMs / Generative AI (prompting, evaluation, or integration)
- Experience in system testing, validation, or QA
- Strong debugging and problem-solving skills
- Excellent written communication skills
- Background in storage administration, SRE, or cloud infrastructure operations
- Experience with MLOps, model evaluation frameworks, or AI testing workflows
- Familiarity with Google Cloud Storage (GCS) or similar platforms
- Experience working in Agile environments with cross-functional teams
What We Do
Careerflow.ai is an AI-powered career management platform and 'career copilot' dedicated to helping job seekers land their dream jobs. The company provides a comprehensive end-to-end toolkit featuring an AI resume builder, LinkedIn profile optimizer, and job tracking tools. By streamlining the application process and optimizing professional profiles, Careerflow helps users navigate the competitive job market and get hired at top tech and startup companies faster.
