Forward Deployed Engineer - Applied AI - Senior - Financial Services - Consulting

Location:

Charlotte, Dallas, New York, Tampa

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** Forward Deployed Engineer - Applied AI - Senior - Financial Services*
* EY is the only professional services firm with a separate business unit ("FSO") that is dedicated to the financial services marketplace. Our FSO teams have been at the forefront of every event that has reshaped and redefined the financial services industry.  If you have a passion for rallying together to solve the most complex challenges in the financial services industry, come join our dynamic FSO team!

The business problems our clients are facing today are not the same problems they have faced in the past. The rapid pace of development in Artificial Intelligence and the technology that enables it has created an urgent need to innovate and adapt to the new global business paradigm. Financial institutions are looking to build smarter and more efficient ways to operate their business, create new revenue streams, and better manage risk, through new opportunities uncovered by their data.

We believe that to fully unlock the potential of Artificial Intelligence, we need to look not only at its application, but also at the strategy level for how best to transform the enterprise into one that is technology and data focused and ready for the new age. Our clients' problems are becoming increasingly complex while at the same time the need to automate and streamline is rising.

** The Opportunity*
* Supports the delivery of solution or infrastructure development services for AI/ML initiatives, applying strong technical capability and hands-on engineering experience. Contributes to the design, development, delivery, and maintenance of AI-enabled solutions or infrastructure while aligning to relevant engineering standards and project delivery expectations. Understands business and user requirements and helps translate them into sound technical designs and implementation plans. Contributes to the integration of AI/ML capabilities into broader enterprise solutions, with a focus on quality, scalability, and user impact.

** Your

Key Responsibilities *
* + Design, develop, test, deploy, and support production-grade AI/ML, generative AI, and intelligent automation solutions.

+ Solve complex technical problems through coding, debugging, testing, troubleshooting, and structured design remediation.

+ Translate business and user requirements into technical designs, APIs, workflows, and supportable implementation patterns.

+ Build and integrate LLM, RAG, and agentic solution components into enterprise applications and platforms.

+ Contribute to system design across service boundaries, orchestration layers, data flows, security controls, and external integrations.

+ Support project delivery through disciplined execution, estimation, documentation, status communication, and risk identification.

+ Partner with Development, Engineering, Product, Data, Architecture, and project leadership teams to deliver high-value AI capabilities.

+ Improve performance, resilience, maintainability, and cost efficiency of deployed AI systems.

+ Participate in architecture and design reviews, providing thoughtful trade-off analysis and implementation input.

+ Use modern AI-assisted software engineering tools such as Claude Code, Codex, or equivalent agentic coding platforms as part of day-to-day engineering delivery.

** AI and Engineering

Skills:

*
* ** Gen AI Foundational:*
* + Ability to understand business challenges and translate them into value-add AI solutions leveraging large language models and intelligent automation

+ Experience designing, building, and maintaining production-grade LLM applications, including end-to-end pipelines from data ingestion through model output delivery (e.g. Azure OpenAI, AWS Bedrock, Google Vertex AI)

+ Demonstrated experience building retrieval-augmented systems that ground model outputs in enterprise knowledge sources, including chunking strategies, embedding pipelines, and retrieval optimization (e.g. Llama Index, Lang Chain, Pinecone, Weaviate, Azure AI Search, pgvector etc.)

+ Knowledge of embedding models, vector search, and semantic retrieval patterns used to ground LLM outputs in enterprise knowledge sources (e.g. OpenAI Embeddings, Azure AI Search, pgvector etc.)

+ Proficiency in prompt engineering techniques including zero-shot, few-shot, chain-of-thought, and structured output design, with the ability to systematically evaluate and iterate on prompt performance(e.g. DSPy, Prompt Flow etc.)

** Agentic and LLM Ops:*
* + Experience designing and building agentic systems including multi-agent orchestration patterns, tool use, and memory design across single and multi-step workflows (e.g. Lang Graph, Auto Gen, CrewAI, Semantic Kernel, NVIDIA NIM etc.)

+ Ability to build reliable agent loops…