Lead Forward Deployed Engineer

About the role

Overview: We are seeking a Lead Forward Deployed Engineer to design and deliver AI-enabled workflows, GenAI applications, and agentic solutions within client environments. This is a senior, hands-on position responsible for translating business processes, data flows, and operational needs into deployable technical solutions. The engineer will lead delivery from initial discovery and technical design through proof of concept, pilot, production rollout, and stabilization while coordinating with AI leads, architects, stakeholders, and engineering teams. This is a six-month contract-to-hire opportunity based in Palm Beach, Florida, with three days onsite each week.

Requirements

Extensive experience in software engineering, application development, solution engineering, or technical consulting, with 10 or more years preferred.

Hands-on experience designing and implementing agentic AI, GenAI, LLM, or RAG-based applications.

Experience conducting client discovery, gathering technical requirements, assessing workflows, and translating business needs into solution designs.

Ability to create technical blueprints for AI automation, application integration, data movement, and workflow orchestration.

Experience integrating AI solutions with enterprise applications, APIs, databases, data platforms, and existing business systems.

Demonstrated ownership of solutions from proof of concept or prototype through pilot, deployment, production support, and performance optimization.

Experience with solution testing, LLM output evaluation, troubleshooting, observability, quality assurance, and performance tuning.

Experience mentoring engineers and establishing reusable technical patterns, libraries, documentation, or engineering standards.

Strong client-facing communication skills with the ability to work across technical, operational, and business stakeholder groups.

Responsibilities

Lead discovery sessions to understand client processes, systems, data flows, technical constraints, and automation opportunities.

Translate business and operational requirements into practical AI solution designs and implementation plans.

Design and build AI-enabled workflows, GenAI applications, RAG solutions, and agentic capabilities.

Configure and orchestrate LLM-powered workflows, tools, prompts, data inputs, outputs, and system interactions.

Integrate AI solutions with enterprise applications, APIs, databases, identity services, and data platforms.

Develop proofs of concept, prototypes, and MVPs before leading pilot execution and production rollout.

Establish testing strategies for functional quality, AI output accuracy, reliability, security, and performance.

Troubleshoot application, model, integration, data-flow, and production issues throughout the delivery lifecycle.

Tune solutions based on user behavior, evaluation results, operational feedback, and production performance.

Document architectures, integration patterns, deployment procedures, reusable components, and engineering standards.

Coordinate delivery activities with AI leads, architects, engineering teams, and client stakeholders.

Mentor engineers and enable client teams to support, maintain, and extend delivered solutions.