
Technology Consulting - TMT - Forward Deployed Engineer - Senior
Posted 3 days ago
The role in short
Build and deploy production-grade generative AI, RAG, and agentic solutions by embedding with client teams and writing production code.
Location: San Antonio, San Francisco, Atlanta, Chicago, Dallas, Houston, and Miami
At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
The opportunity
#TechnologyConsulting #AI
At EY Consulting, we help Technology companies transform through the power of people, technology, and innovation. Our AI Engineering and Solutions team builds Tech Sector Transformative solutions. These are production AI systems that change how software, cloud, semiconductor, cybersecurity, and digital-platform companies operate and grow.
As a Senior and Forward Deployed Engineer (FDE), you will help build our FDE capability from the ground up. You will work alongside client teams, write production code, and deliver AI systems that fit how work gets done in the client environment. You will grow across four disciplines: software engineering, AI and platform fluency, sector knowledge, and customer leadership.
This role is not additional delivery capacity. It is a different kind of talent. Each engagement should create value that compounds: a project becomes a solution pattern, the pattern becomes a sector playbook, the playbook becomes a platform primitive, and the platform primitive becomes a competitive advantage for EY and our clients.
Your key 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.
Skills and attributes for success
To qualify for the role, you must have:
- 5+ years of applied engineering experience, including meaningful experience in AI/ML engineering roles.
- LLM depth, not just API usage. Strong understanding of LLMs, advanced prompt engineering, and generative AI delivery patterns.
- Applied AI engineering with a safety mindset. Experience building production-grade RAG systems, including retrieval, grounding, ranking, and guardrails.
- Workflow-centric AI design. Familiarity with agentic systems and multi-step AI workflows.
- Strong systems and performance orientation across APIs, services, asynchronous workflows, and cloud-native patterns.
- Full-stack and infrastructure skills. Strong hands-on Python or Java, exposure to Azure, AWS, and/or GCP, and CI/CD using GitHub or Azure DevOps.
- Customer-facing ambiguity handling. 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.
- Candidates must be legally authorized to work in the U.S. without the need for employer sponsorship, now and in the future
Ideally, you will have:
- Platform thinking. Interest in building reusable components rather than one-off solutions.
- Data and lakehouse skills. Experience with embedding models, vector search, and platforms such as Databricks, Snowflake, or Microsoft Fabric.
- Structured reasoning and evaluation. Experience with benchmarking, A/B testing, offline quality assessment, and production monitoring.
- Architect-level customer guidance in design discussions.
- Field engineering and enablement. 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.
What we offer you
At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers.
- The salary range for this job is:
- New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $122,900 to $204,900
- Bay Area California offices – $128,100 to $213,400
- All other offices locations in the US, including Sacramento – $102,500 to $187,900
- Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
Are you ready to shape your future with confidence? Apply today.
- To make the most of your application experience, please limit yourself to two applications within a six-month period.
- EY accepts applications for this position on an on-going basis.
- For those living in California, please click here for additional information.
- At EY, our values set the foundation for how we work and the behaviors we expect of our people. Any misrepresentation or falsification of information or lack of integrity at any point in the recruiting process may result in withdrawal of your candidacy, revocation of an offer or immediate termination of employment.
EY | Building a better working world
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
All in to shape the future with confidence.
EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.
EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at ssc.customersupport@ey.com.
Prep for this interview
5 questions likely to come up at EY, each matched to a line in this posting.
- 1LLMs, RAG and agents
They wrote: “LLM depth, not just API usage. Strong understanding of LLMs, advanced prompt engineering, and generative AI delivery patterns.”
When would you fine-tune a model, and when is prompting or retrieval enough?
How to answer
Why they ask: Customers often ask for fine-tuning first. They want to hear you pick the cheapest thing that works.
- Try clear prompts and examples first; measure against a test set
- If the model lacks the customer's facts, add retrieval
- Fine-tune when you need a format or behaviour prompts can't hold, and you have good examples
- Count the cost: training data, upkeep and re-testing on every model update
Tip: Start from what's wrong: missing knowledge points to retrieval, wrong style or format points to fine-tuning.
- 2Cloud, deployment and security
They wrote: “Full-stack and infrastructure skills. Strong hands-on Python or Java, exposure to Azure, AWS, and/or GCP, and CI/CD using GitHub or Azure DevOps.”
How would you debug a deployment that works in staging but fails at the customer's site?
How to answer
Why they ask: Customer environments differ in ways you can't see. This tests method under pressure.
- Compare versions, config and environment variables
- Check network rules, proxies and certificates (common in enterprise)
- Look at resource limits and permissions
- Add the missing check to your install steps afterwards
Tip: List the usual suspects and how you'd check each without full access.
- 3Discovery and scoping
They wrote: “Customer-facing ambiguity handling. Comfort working directly with client stakeholders when requirements are unclear.”
Tell me about a time the customer asked for one thing but needed another.
How to answer
Why they ask: Good FDEs spot when a request is a guess at a solution. They want proof you can redirect a customer without losing their trust.
- What they asked for, and the detail that made you doubt it
- How you tested the doubt (shadowed users, looked at logs, ran a quick prototype)
- How you made the case to the customer
- What shipped and what changed for them
Tip: Pick a story where you checked your hunch with data or users before pushing back.
- 4Integrations and APIs
They wrote: “Translate business requirements into technical designs, APIs, workflows, and user stories.”
Walk me through connecting our product to a customer's internal system that has no documentation.
How to answer
Why they ask: This happens weekly in the job. They want a calm, step-by-step method.
- Find who owns the system and get read access to a test environment
- Watch real traffic or logs to learn the data shapes
- Build a thin adapter with logging around every call
- Agree on how failures get reported, and who fixes what
Tip: Talk about finding the owner of the system first. The code is the easy part.
- 5Coding
They wrote: “We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.”
Build a small in-memory cache. Then add expiry. Then a size limit.
How to answer
Why they ask: Staged exercises show how your code holds up when requirements change mid-interview, like at a customer.
- Start with get and set on a dictionary, plus tests
- Store an expiry time with each value and check it on read
- Track use order and evict the least recently used entry when full
- Say what you'd change for many threads or many machines
Tip: Keep the first version simple and well tested so the next stage is a small change.
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