Forward Deployed Engineer

About the role

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.

Responsibilities

• Build on the Enterprise GPT Platforms
• Design and ship agents and multi-step workflows using Glean, Claude, and other GPT platforms and applying platform tools such as Agent Builder, actions, MCP tools, and adjacent automation (e.g., n8n, Zapier, Make)
• Apply AI solution patterns such as retrieval-augmented generation (RAG), workflow orchestration, agent-assisted processes, model integration, API-based automation, and human-in-the-loop review
• Create connections to ingest data from enterprise systems like Salesforce, ServiceNow, SharePoint/Teams, email, and internal APIs
• Extend platform capabilities through MCP-based integrations and context-aware workflows that improve the usefulness and reach of AI solutions
• Create custom services and integrations, including REST APIs and webhooks, when platform-native patterns or existing automations are not sufficient
• Ensure solutions are secure, reliable, observable, and compliant with enterprise standards
• Create reusable templates, components, and solution patterns that can be applied across teams and use cases
• Identify and solve business friction points
• Proactively surface pain points across business workflows and reimagine them leveraging the best available technology to create impact
• Rapidly prototype, validate with real users, and harden MVPs into scalable, production solutions
• Partner with stakeholders to prioritize high-impact use cases based on business value, feasibility, risk, and repeatability, with a focus on scalable solutions rather than one-offs
• Measure and communicate the value of solutions delivered, including time saved, errors reduced, adoption, reliability, and operational performance
• Own LLM Quality, Telemetry & Cost
• Apply production LLM practices: prompt and agent design, guardrails, and evaluation
• Instrument usage, reliability, and token/credit consumption at the agent and team level
• Use data to improve quality and reduce unnecessary spend (context scoping, summarization, caching, model choice)

Requirements

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

Preferred Experience

• Familiarity with common business systems such as Salesforce, Microsoft 365, SharePoint, Teams, ServiceNow, ticketing or ITSM platforms, and CRM or ERP tools
• Hands-on experience with Enterprise GPT platforms (e.g., Glean, Claude) and automation tools (e.g., n8n, Zapier, Make)
• Familiarity with enterprise security concepts such as RBAC, least privilege, SSO, SAML, OAuth, OIDC, and auditability
• Experience working in cross-functional delivery teams that pair solution building with business process transformation, user enablement, and change support

How You Work

• 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

Pay

$160,000 - $190,000 a year

Schedule

Full-time

Benefits

USA Employment Benefits Include Medical, Dental, and Vision Insurance
401(k)
Paid company holidays
Paid time off
Paid parental and caregiver leave
Plus more!

See benefits here.