AHEAD is a company that builds platforms for digital business, focusing on cloud infrastructure and AI transformation. They are seeking a Forward Deployed Engineer to design, build, and run production AI applications, collaborating with cross-functional teams to support enterprise solutions.
Responsibilities:
- 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 automations (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
- Implement 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
- 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
- Apply production LLM practices: prompt and agent design, guardrails, and evaluation
- Use test sets, quality metrics, and offline or online evaluation methods to improve solution performance over time
- 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
- 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
- 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