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

About the role

The opportunity involves leading the definition and delivery of AI system design principles, reference architectures, and engineering standards for highly complex AI/ML initiatives across the organization. This role requires hands-on engineering experience and the ability to shape long-term technology direction.

Responsibilities

• Define and govern system design principles, reference architectures, and engineering patterns for AI/ML, generative AI, RAG, and agentic systems.
• Lead the most complex and escalated technical challenges across multiple teams, providing hands-on guidance in architecture, coding, troubleshooting, and design remediation.
• Own end-to-end architecture for strategic AI initiatives, including service boundaries, orchestration models, data contracts, evaluation frameworks, and operational guardrails.
• Drive consistency in engineering standards, design reviews, architecture governance, observability, resilience, security, and responsible AI practices.
• Shape the enterprise integration model for AI/ML components within broader product, platform, infrastructure, and client delivery ecosystems.
• Define and evolve API and integration strategies for AI platforms and applications, including contract design, versioning, security, idempotency, and reliability patterns at enterprise scale.
• Ensure API layers and application integration patterns decouple clients from internal AI service topology, enabling safe evolution of models, workflows, and data stores without breaking consumers.
• Lead large, complex project or program delivery outcomes by aligning architecture decisions, engineering execution, stakeholder governance, risks, dependencies, and delivery quality.
• Influence platform strategy, technical roadmaps, and investment decisions through deep engineering judgment and practical delivery insight.
• Partner with senior leaders across Engineering, Architecture, Product, Data, Security, Operations, and engagement leadership to align strategy with execution.
• Establish scalable approaches for model evaluation, benchmarking, experimentation, rollout controls, and production quality measurement.
• Mentor senior engineers and technical leads, raising the organization's bar for system design, technical depth, delivery rigor, and architectural decision-making.
• Identify opportunities to reduce duplication, accelerate delivery, and create reusable AI platform capabilities across the enterprise.

Requirements

The role demands a strong foundation in gen AI, advanced hands-on engineering experience, and expertise in Python. It also requires experience in knowledge AI systems, agentic design, and LLM Ops. Candidates should have a proven track record in enterprise-scale AI platform strategy, data security, and compliance practices.

Qualifications

• Bachelor’s degree preferred.
• 10+ years of applied engineering experience, including extensive experience in senior AI/ML engineering, architecture, or complex technology delivery roles.

Skills

• Gen AI Foundational: Ability to translate complex enterprise business challenges into strategic AI architecture decisions, balancing immediate delivery needs with long-term platform scalability and firmwide adoption.
• Advanced hands-on engineering credibility in Python, guiding architecture and implementation decisions across senior engineering teams.
• Expertise in designing and governing enterprise agentic AI frameworks, including multi-agent orchestration, tool use patterns, and memory architecture.
• Experience integrating external vendor tooling for model monitoring, observability, safety, and compliance into enterprise AI platforms.
• Ability to define and enforce LLM Ops standards across the enterprise, including model lifecycle governance, deployment pipelines, versioning strategies, and continuous improvement frameworks.
• Ability to identify opportunities to reduce duplication, accelerate delivery, and create reusable AI platform capabilities and reference architectures that can be adopted across multiple teams and client engagements.
• Ability to define and govern API strategy, containerization, and integration standards for enterprise AI platforms, ensuring AI service consumers are decoupled from internal model and workflow topology.
• Proven track record of building and delivering large-scale enterprise AI platforms, balancing hands-on technical contribution with cross-functional coordination and stakeholder alignment.
• Experience governing data security, privacy, and compliance practices as they apply to enterprise LLM and agentic system development and deployment.
• Strong ability to communicate complex AI architecture concepts to executive, technical, and non-technical audiences and translate strategic direction into actionable engineering roadmaps.
• Clear communicator able to explain complex AI system behavior and trade-offs to technical and non-technical stakeholders, including risk and compliance.
• Comfort with ambiguity, able to operate effectively as requirements, regulations, and technologies evolve.
• Collaborative and cross-functional, working closely with engineering, product, risk, legal, and audit teams.
• Sound judgment in regulated environments, with awareness of risk, controls, and when human oversight is required.

Benefits

At EY, we offer a range of benefits to support your well-being and career growth, including:

• Flexible work arrangements
• Professional development opportunities
• Competitive compensation and benefits package
• Employee resource groups
• Work-life balance programs

Pay

Compensation is competitive and commensurate with experience.

Schedule

Full-time position available.