The Forward Deployed Engineer (FDE) is a hands-on role embedded within AHEAD's internal AI transformation function. You will design, build, and run production AI applications on enterprise GPT platforms, including custom agents, workflows, connectors, and integrations. You will operate as the technical build resource within a cross-functional delivery team, partnering closely with business stakeholders, a transformation consultant, and an adoption lead to support one of AHEAD’s key domains, such as Services, Go-to-Market, or Corporate & Technology. This person owns the full solution lifecycle from discovery and design through build, rollout, optimization, and ongoing support.

This role is well suited for someone who enjoys working directly with business teams, translating ambiguous needs into practical AI-enabled solutions, and building production AI patterns such as orchestration, model integration, evaluation, observability, and secure enterprise deployment. Success in the role requires comfort working inside a shared team model where solution design, user adoption, and business outcomes are delivered in close coordination rather than in isolation.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data and Analytics

• Experience in technical roles such as Forward Deployed Engineer, Solutions Engineer, Integration Engineer, Automation Engineer, or similar roles with direct stakeholder engagement

• Experience designing or supporting AI-enabled solutions in production environments, prompting and system design, agent development, and workflow configuration

• Familiarity with evaluation approaches such as test sets, quality metrics, and iterative improvement loops

• Working knowledge of AI solution patterns such as retrieval-augmented generation, orchestration, model integration, vector-backed retrieval, and human-in-the-loop workflows

• Ability to configure existing connectors to access required data

• Experience integrating enterprise applications using APIs, webhooks, automation tools, or lightweight services

• Familiarity with observability, monitoring, governance, guardrails, and responsible AI controls in enterprise environments

• Operate as a builder and long-term advisor, not just an implementer

• Comfortable being embedded with business teams while upholding platform and security standards

• Communicate clearly with executives and non-technical stakeholders about trade-offs, risks, and impact

• Move fast on prototypes, but know when to slow down for risk, security, or cost

• Stay current on the cutting edge of AI — new models, MCP developments, agentic frameworks, and emerging tooling — and bring relevant innovations back to AHEAD

• Continuously scan the business for friction points and unmet needs; show up with ideas, not just execution

• Work effectively as part of a small, embedded team where technical build, business problem framing, and adoption support are closely coordinated