EYEY - GDS Consulting - AI and DATA - Forward Deployed engineer - Associate Director
About this role
The opportunity
We are seeking a Associate Director for Forward Deployed Engineer (FDE) with 15+ years of deep, hands-on engineering experience to design, build, and deploy AI-powered solutions directly with clients. This role is ideal for an elite individual contributor who thrives in ambiguous environments, prefers building real systems over managing teams, and can translate business problems into production-grade AI solutions. The individual should have worked on GenAI, AI/ML, Data Science solutions on multiple proprietary enterprise AI tech stacks along with Hyperscalers, Platform AI tech stack.
Role Purpose:
- Lead complex end-to-end deployments in production at strategic customers.
- Act as a forward-deployed technical owner, responsible for taking ambiguous ideas from concept → prototype → production.
- Lead the discovery, design, development, and deployment of high-impact AI / GenAI-powered solutions in close collaboration with client stakeholders.
- Build LLM-driven applications, RAG systems, and agentic workflows that demonstrate measurable business value.
- Drive innovation by creating reusable accelerators, frameworks, and reference implementations for enterprise GenAI deployments.
- Enable rapid experimentation and large-scale adoption of AI, data, and cloud platforms through hands-on engineering leadership.
Key Responsibilities
- Embed directly with clients to understand business and technical challenges.
- Break down vague or high-level problem statements into executable engineering solutions.
- Own solution outcomes end-to-end, from discovery to production deployment.
- Operate as a trusted technical advisor to senior client stakeholders.
- Design and build LLM-powered applications (chatbots, copilots, assistants), Retrieval-Augmented Generation (RAG) systems & Agentic workflows and orchestration pipelines
- Integrate LLMs with enterprise data platforms, APIs, and external systems.
- Evaluate and optimize trade-offs across latency, cost, accuracy, scalability, and security.
- Iterate rapidly based on client feedback.
- Convert PoCs into production-grade, enterprise-ready deployments.
- Design systems for scalability, reliability, and observability.
- Build reusable engineering accelerators, frameworks, and reference architectures.
- Codify best practices for enterprise GenAI deployments.
- Collaborate with internal teams to transition deployed solutions into long-term support and scale.
- Develop cloud-native architectures across Azure, AWS, or GCP.
Required Skills & Experience
Mandatory
- 15+ years of experience in software engineering, data engineering, or AI/ML.
- Strong hands-on system-building and production deployment experience.
- Proven experience delivering solutions in client-facing or high-ambiguity environments.
- Solid understanding of Distributed systems, Microservices and APIs & Cloud-native architectures
- Ability to independently own and deliver complex, high-impact solutions.
- Excellent communication skills with both technical and business stakeholders.
Desired / Preferred
- Hands-on experience with LLM APIs and prompt engineering, RAG architectures and vector databases, Agentic workflows and orchestration frameworks
- Experience integrating AI systems with enterprise data platforms.
- Exposure to AI ecosystem – OpenAI, Claude, Cursor, Palantir, and many others along with Hyperscalers – Azure, AWS, GCP, and similar ecosystem.
- Experience with DevOps, CI/CD pipelines, and infrastructure automation.
- Prior Forward Deployed Engineer / Solutions Engineer / Field Engineer background.
- Experience building 0 → 1 AI or data products.
- Exposure to MLOps practices and model monitoring.
- Frontend or UI exposure for AI-driven applications.
What This Role Is NOT
- Not a people management role
- Not a delivery governance or program management role
- Not limited to architecture reviews — you are expected to build and ship
What we look for
- Deep technical expertise with genuine enthusiasm for building and learning.
- Strong ownership mindset with bias toward action.
- Comfort in fast-moving, unstructured environments.
- Strong communication with both engineers and business leaders
Success Metrics (First 6–12 Months)
- Deliver 2–4 production-grade AI use cases for clients
- Demonstrate measurable business impact (efficiency, revenue, cost savings)
- Establish credibility as a go-to FDE for complex engagements
- Create reusable patterns for scaling similar solutions
What working at EY offers
At EY, we’re dedicated to helping our clients, from start-ups to Fortune 500 companies — and the work we do with them is as varied as they are.
You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer:
- Support, coaching and feedback from some of the most engaging colleagues around
- Opportunities to develop new skills and progress your career
- The freedom and flexibility to handle your role in a way that’s right for you
EY | Building a better working world
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
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