Data Engineer

Fractal; New Jersey; Remote; USD 120,000 - 160,000; Full time

Job summary

Fractal is seeking an experienced Data Engineer to support a large-scale AI, Data, and Analytics transformation within a leading Financial Services organization. The role focuses on platform modernization, AI Gateway migration, BI transformation, and cloud-native data engineering using Claude LLM, OpenAI Custom GPTs, AWS, Tableau, and Alteryx.

The candidate will help define strategy and execute migrations of enterprise AI and analytics platforms, contributing to a scalable AI ecosystem while

Responsibilities

• Platform Migration & Modernization: design and implement migration strategies for data, analytics, and AI platforms to AWS.
• AI Gateway Engineering & Migration: build and migrate enterprise AI Gateway capabilities with governance and secure access.
• AI Evaluation Framework & Tool Development: define evaluation and testing for GenAI apps and LLM-powered solutions.

Skills

Cloud data engineering

Data architecture

Big data processing

Tools

AWS

Tableau

Alteryx

Claude LLM

OpenAI Custom GPTs

AWS Bedrock

Job description

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.

Location: Remote (supporting EST hours)

Role Summary

We are seeking an experienced Data Engineer to support a large-scale AI, Data, and Analytics transformation initiative within a leading Financial Services organization. This role will be responsible for driving platform modernization, AI Gateway migration, BI transformation, AI evaluation framework development, and cloud-native data engineering. The successful candidate will play a key role in supporting the organization’s AI ecosystem built on Claude LLM, OpenAI Custom GPTs, AWS, Tableau, and Alteryx, while helping define strategy and execute the migration of enterprise AI and analytics platforms.

Key Responsibilities

Platform Migration & Modernization

• Design and execute migration strategies for enterprise data, analytics, and AI platforms to AWS cloud environments.
• Assess legacy architectures and define target-state data and AI platform architectures.
• Lead migration planning, implementation, testing, and production deployment activities.
• Optimize platform performance, scalability, resiliency, and operational efficiency.
• Develop migration roadmaps and implementation plans aligned with business and technology objectives.

AI Gateway Engineering & Migration

• Design, develop, and support enterprise AI Gateway solutions enabling governed access to AI services.
• Lead the migration of AI Gateway capabilities from Portkey to Apigee, including architecture design, implementation planning, and execution.
• Develop and maintain integration frameworks connecting enterprise applications to: Claude LLMOpenAI Custom GPTsAWS Bedrock and AI services
• Implement authentication, authorization, observability, rate limiting, usage tracking, and audit capabilities.
• Create reusable APIs and services that enable secure and scalable AI adoption across the organization.
• Establish operational monitoring and governance controls for AI platform usage.

AI Evaluation Framework & Tool Development

• Define enterprise AI evaluation, testing, and validation frameworks for GenAI applications, AI agents, and LLM-powered solutions.
• Build evaluation tooling and automation capabilities covering: Functional testingAccuracy testingHallucination detectionPrompt evaluationGroundedness verificationSafety and toxicity testingBias and fairness assessmentRegression testingAgent workflow validationPerformance benchmarking
• Develop evaluation datasets, benchmark suites, scoring methodologies, and approval criteria.
• Implement automated testing pipelines integrated into