Overview

We are seeking a highly technical and business-facing Forward Deployed Agentic Engineer to help drive enterprise GenAI initiatives in a fast-moving, high-visibility environment. This role is ideal for engineers and architects currently working in large enterprise consulting or financial environments who want to move closer to real-world AI deployment, rapid innovation, and business impact.

This is not a traditional support or maintenance role. This position sits at the intersection of AI strategy, solution architecture, rapid prototyping, and enterprise execution. The team operates in fast-paced sprint cycles, partnering directly with engineering, data, security, and business stakeholders to build and operationalize AI-powered solutions.

The ideal candidate has experience translating ambiguous business problems into scalable GenAI solutions and is comfortable operating in undefined environments where speed, iteration, and pragmatic decision-making matter.

What You’ll Be Doing

• Design and document enterprise GenAI solution architectures across multiple initiatives
• Build and support AI-powered workflows leveraging LLMs, agentic orchestration, and enterprise integrations
• Partner closely with engineering, security, risk, and business teams to align AI solutions with enterprise standards
• Conduct rapid development sprints and iterate quickly on AI use cases and prototypes
• Define current state, interim state, and target state architecture designs
• Create architecture diagrams, integration patterns, and technical decision documentation
• Integrate AI platforms with APIs, enterprise systems, data pipelines, and cloud environments
• Support architecture governance, design reviews, and technical approvals
• Translate highly technical AI concepts into clear business-facing documentation and presentations
• Drive scalable patterns for AI adoption across enterprise platforms and workflows

Required Experience

• Strong experience in Solution Architecture, Enterprise Architecture, or AI-focused Architecture roles
• Hands-on experience with Generative AI technologies and Large Language Models (LLMs)
• Strong Python development experience
• Experience building AI integrations, agentic workflows, or LLM-enabled enterprise applications
• Experience with AI orchestration frameworks such as LangChain, LangGraph, or similar
• Familiarity with Retrieval Augmented Generation (RAG) concepts and enterprise AI patterns
• Experience working with APIs, event-driven architectures, and enterprise integrations
• Cloud architecture experience in AWS, Azure, or GCP
• Strong ability to document architecture decisions, workflows, and system integrations
• Experience with architecture and diagramming tools such as Visio, Lucidchart, or Draw.io
• Excellent communication skills with the ability to work across technical and non-technical stakeholders

Ideal Background

• Engineers or architects from enterprise consulting organizations or large-scale enterprise technology environments
• Candidates who have worked on AI modernization, digital transformation, or enterprise innovation initiatives
• Individuals comfortable working directly with business stakeholders instead of isolated engineering teams
• Professionals who thrive in ambiguity, rapid iteration, and highly visible delivery environments
• Experience supporting enterprise AI adoption, governance, and operationalization efforts

Preferred Experience

• Experience building or deploying AI agents in production environments
• Exposure to multi-agent orchestration or autonomous workflow systems
• Experience integrating OpenAI, Anthropic, or enterprise AI platforms
• Familiarity with AI governance, observability, and enterprise risk considerations
• Experience working in highly regulated enterprise environments
• Consulting background strongly preferred

Why This Opportunity Stands Out

• Highly visible enterprise AI initiatives with executive sponsorship
• Opportunity to work on cutting-edge GenAI and agentic AI solutions
• Fast-moving environment focused on innovation and rapid delivery
• Blend of architecture, engineering, and business engagement
• Direct impact on enterprise AI transformation strategy
• Opportunity to shape scalable AI patterns and future-state architecture across the organization