Technology Consulting - TMT - Forward Deployed Engineer - Senior

EY•Atlanta, GA

7d•$102,500 - $213,400

About The Position

EY Consulting’s AI Engineering and Solutions team builds production AI systems that help technology companies across software, cloud, semiconductors, cybersecurity, and digital platforms transform how they operate and grow. As a Senior Forward Deployed Engineer, you will help build EY’s forward-deployed engineering capability, working alongside client teams, writing production code, and delivering AI systems suited to client environments and workflows. The role develops expertise across software engineering, AI and platform fluency, sector knowledge, and customer leadership. Engagements are expected to generate reusable solution patterns, sector playbooks, and platform capabilities that create lasting value for EY and its clients. The role is based in San Antonio, San Francisco, Atlanta, Chicago, Dallas, Houston, or Miami. In-person work at an EY office and/or client location may be required up to 50% of the time, based on client and project needs. EY accepts applications on an ongoing basis.

Requirements

5+ years of applied engineering experience, including meaningful experience in AI/ML engineering roles.
Strong understanding of LLMs, advanced prompt engineering, and generative AI delivery patterns.
Experience building production-grade RAG systems, including retrieval, grounding, ranking, and guardrails.
Familiarity with agentic systems and multi-step AI workflows.
Strong systems and performance orientation across APIs, services, asynchronous workflows, and cloud-native patterns.
Strong hands-on Python or Java skills.
Exposure to Azure, AWS, and/or GCP.
Experience with CI/CD using GitHub or Azure DevOps.
Comfort working directly with client stakeholders when requirements are unclear.
Ability to work in person at an EY office and/or client location up to 50% of the time, based on client and project needs.
Legally authorized to work in the U.S. without the need for employer sponsorship, now and in the future.

Nice To Haves

Interest in building reusable components rather than one-off solutions.
Experience with embedding models, vector search, and platforms such as Databricks, Snowflake, or Microsoft Fabric.
Experience with benchmarking, A/B testing, offline quality assessment, and production monitoring.
Ability to provide architect-level customer guidance in design discussions.
Experience helping client teams adopt the tools you build.
High-trust client relationships built over one or more engagements.
Experience supporting software, cloud, semiconductor, cybersecurity, digital-platform, media technology, or AI-native organizations.
Experience with Kubernetes, Docker, GPU-accelerated workloads, or orchestration frameworks such as LangGraph, LangChain, or Semantic Kernel.
Microsoft, Google Cloud, or AWS certifications.
Bachelor’s degree in computer science, engineering, or a related field.

Responsibilities

Work alongside client teams to understand requirements and build AI solutions that fit their processes and constraints.
Design, develop, test, deploy, and support production-grade generative AI, RAG, and agentic solutions.
Solve complex technical problems through coding, debugging, testing, and structured design remediation.
Translate business requirements into technical designs, APIs, workflows, and user stories.
Contribute to system design across service boundaries, orchestration layers, data flows, security controls, and integrations.
Add evaluation, monitoring, and safety checks to the solutions you build.
Support delivery through estimation, documentation, status communication, and risk identification.
Contribute reusable code, solution patterns, and demonstrations to proposals and to the practice.
Use AI-assisted engineering tools such as Claude Code, Codex, or equivalent as part of day-to-day engineering delivery.