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# Forward Deployed Data and AI Tech Lead

- **Company:** Ernst & Young LLP
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Engineering, Python (Programming Language), Data Processing, Google Cloud, Large Language Models, Generative AI, Agentic-AI, Containerization, Infrastructure Automation Frameworks, Information Technology, Machine Learning Operations
- **Published:** November 13, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pyvy61yt9o

## About the Role

* Bachelor's degree in Computer Science, Engineering or a related field with approximately 8+ years of hands-on software, data or AI engineering experience, including technical or team leadership responsibilities.
 * Proven experience delivering data or AI solutions from prototype to real-world adoption.
 * Strong Python programming skills and solid software engineering fundamentals.
 * Experience across multiple areas including data processing and pipelines, AI/ML workflows, LLM and agentic AI frameworks, and Retrieval-Augmented Generation (RAG) solutions.
 * Hands-on experience with cloud engineering, preferably Microsoft Azure, as well as AWS and/or Google Cloud, including infrastructure-as-code practices.
 * Experience working directly with business stakeholders in consulting, product or forward-deployed environments.
 * Excellent communication skills with the ability to engage effectively with both business and technical audiences.
 * Ability to thrive in ambiguity, demonstrate strong business acumen and take ownership of outcomes.

## Description

* Embed directly with client business teams to identify, frame and prioritise high-value data and AI opportunities.
 * Design, prototype and demonstrate working solutions spanning data processing, data products, AI/ML workflows and agentic AI solutions using cloud-native technologies.
 * Lead a pod of forward-deployed engineers, providing technical direction, reviewing work and removing delivery obstacles while remaining hands-on in development.
 * Make pragmatic build, pivot or stop decisions based on business value and validated learning.
 * Translate validated prototypes and requirements into scalable, production-ready delivery opportunities.
 * Build trusted relationships with client stakeholders and bridge business and technical perspectives.
 * Promote responsible AI and compliance-by-design principles from the earliest stages of solution development.
 * Mentor and develop engineers while contributing to reusable assets, accelerators and engineering best practices.