GenAI Forward Deployed Engineer (client facing) - Financial Services

Continuum Resource Network•Atlanta, GA

About The Position

The GenAI Forward Deployed Engineer will lead workstreams within larger AI transformation programs, work directly with client stakeholders, and contribute to solution design across Generative AI, Agentic AI, and machine learning use cases in Financial Services, including fraud detection, AML, credit risk, payments intelligence, and customer experience. The role involves translating business requirements into AI solution frameworks and driving day-to-day delivery with cross-functional teams. The position manages end-to-end AI transformation workstreams from opportunity framing through deployment and value realization. It supports executive-level AI strategy discussions, facilitates discovery sprints and AI readiness workshops under senior leadership, develops business cases tied to measurable outcomes, and tracks milestones, risks, dependencies, and reporting. The role contributes to designs for GenAI applications, Agentic pipelines, RAG systems, and production ML, taking Financial Services regulatory and risk requirements into account. It coordinates with solution leads, AI engineers, data scientists, and ML platform engineers, and documents architectures, technical requirements, and integration patterns for client environments. It also supports account growth, thought leadership, mentoring, and reusable delivery assets.

Requirements

At least 6 years of experience across AI/ML, data science, or enterprise digital transformation, including client-facing delivery roles.
Solid working knowledge of Generative AI, including LLMs, RAG, and fine-tuning.
Solid working knowledge of Agentic AI, including multi-agent orchestration and workflow automation.
Track record managing complex AI delivery workstreams at large enterprises from strategy through production.
Ability to engage credibly with business stakeholders and engineering teams.
Strong communication skills and ability to make complex AI concepts accessible to diverse audiences.

Nice To Haves

Financial Services domain expertise in banking, payments, capital markets, or fintech, with hands-on AI application to AML, fraud, credit risk, or payments.
Familiarity with Financial Services regulatory and risk frameworks and explainability requirements.
Background at an AI-native company, enterprise AI lab, or as an AI or engineering practitioner within a Financial Services firm.
Strong technical foundation in AI/ML demonstrated through hands-on work, published projects, or equivalent practical expertise.

Responsibilities

Manage end-to-end workstreams within AI transformation programs, from opportunity framing through deployment and value realization.
Support executive-level AI strategy conversations and facilitate discovery sprints and AI readiness workshops under senior leadership.
Develop business cases connecting AI capabilities to measurable financial and operational outcomes.
Track program milestones, risks, and dependencies, and maintain clear reporting to client stakeholders and internal leadership.
Contribute to AI solution designs spanning GenAI applications, Agentic pipelines, RAG systems, and production ML, accounting for Financial Services regulatory and risk requirements.
Coordinate with Solution Leads and cross-functional teams, including AI engineers, data scientists, and ML platform engineers, to drive scalable, compliant AI deployments.
Document solution architectures, technical requirements, and integration patterns for client environments.
Identify account expansion opportunities and support technical scoping and ROI modelling for new engagements.
Contribute to thought leadership content and represent the company at Financial Services AI events.
Mentor junior team members and contribute to delivery playbooks and reusable IP accelerators.