Forward Deployed AI Engineer - Associate Director

About the role

The opportunity involves supporting the design, development, and deployment of AI-driven, data-centric solutions within strategic client environments. This role combines strong technical expertise with emerging leadership capabilities to drive business impact through collaboration with client teams and internal stakeholders.

Responsibilities

• Collaborate with senior client stakeholders and technical teams to support AI and data strategy initiatives.
• Assist in the full lifecycle of solution development—from problem definition, architecture design, prototyping, deployment, to scaling and adoption.
• Help align client technology roadmaps with business objectives and emerging AI trends.
• Develop and implement AI and LLM-powered applications leveraging Retrieval-Augmented Generation (RAG), autonomous agents, and orchestration frameworks.
• Demonstrate proficiency in Python and agent frameworks such as LangChain, LlamaIndex, or AutoGen.
• Rapidly develop functional prototypes and production-ready demos within project timelines.
• Support identification and pursuit of technical expansion opportunities to accelerate account growth.
• Contribute to proposal development, technical demos, and client engagements by articulating AI/ML capabilities and business value.
• Communicate effectively with both technical and non-technical stakeholders.
• Mentor and guide junior engineers and data scientists within cross-functional pods.
• Foster a culture of innovation, agility, and continuous improvement.
• Contribute to the refinement of EY’s Forward Deployed Engineering frameworks, best practices, and technical capabilities.

Qualifications

• 6+ years in software engineering, data engineering, or AI/ML solution delivery.
• Proven experience delivering scalable AI/ML solutions in client-facing or collaborative roles.
• Solid expertise in machine learning, generative AI, NLP, computer vision, data platforms, and big data technologies.
• Experience with cloud-native development, microservices, container orchestration (Kubernetes, Docker).
• Proficiency with cloud platforms: Azure, AWS, GCP.
• Familiarity with DevOps practices including CI/CD, Infrastructure as Code (Terraform, Ansible), monitoring, and logging.
• Exposure to agentic architectures, multi-agent orchestration, or cognitive harness patterns.
• Consulting or technical delivery experience with enterprise clients.
• Demonstrated ability to contribute to complex technical engagements and collaborate with multidisciplinary teams.

Skills

• Ability to operate effectively in ambiguous, fast-paced client environments.
• Strong hands-on AI/ML engineering skills combined with emerging solution leadership capabilities.
• Excellent communication and stakeholder management skills.
• Commercial awareness focused on delivering measurable business outcomes.
• Passion for AI, cloud-native architectures, and emerging technologies.