Forward Deployment Engineer

Job Title-  Forward Deployment Engineer

Location-  Edison-NJ, Milford-OH, Chicago-IL

Salary Range-  70k to 90k

Build working prototypes and proof-of-concepts (POCs) for Agentic AI use cases across enterprise IT domains · Develop platform-agnostic solutions leveraging APIs, LLM frameworks, and cloud-native services · Implement lightweight, cost-efficient demo architectures using serverless and managed services · Integrate components such as: o AI agents (reasoning, orchestration, automation) o Knowledge fabric / data pipelines o Workflow automation and observability layers · Design and build demos aligned to key enterprise domains: · Infrastructure & Cloud Engineering o Provisioning, monitoring, automation, and scaling scenarios · Service Desk & End User Services o Ticket triaging, virtual agents, self-healing workflows · Network Operations o Event correlation, anomaly detection, automated remediation · Build quick-turnaround demo environments for multiple opportunities simultaneously · Continuously refine prototypes based on feedback · Maintain reusable demo assets, scripts, and templates · Ensure demos are scalable, repeatable, and easy to deploy · Work with Solution architects, Sales / business teams and Platform teams

Qualification and Specialization:

Bachelor’s degree in computer science, IT, Engineering

Unique Experience from this Role:

· Work hands-on with Agentic AI, multi-agent systems, and automation workflows · Build end-to-end prototypes (not isolated features) covering: o Data → AI agents → workflows → outcomes · Exposure to enterprise-grade architectures (knowledge fabric, orchestration layers, observability) · Participate in customer demos, solution positioning, and deal pursuits · Gain early exposure to: o Customer pain points o Competitive differentiation o Value articulation · Create multiple MVPs and demo-ready prototypes continuously · Contribute to a portfolio of innovation assets and reusable Ips · Design solutions that work across: AWS / Azure / GCP · Learn interoperability, abstraction layers, and avoiding vendor lock-in · Learn to Convert technical builds into business narratives and Demonstrate ROI, efficiency, and transformation outcomes

Learning outcomes for the Trainee:

· Convert business problems into Solution architecture, Working prototype, Demo-driven value story · Learn how to build complete systems, not just components · Learn how modern architecture is built using: o Knowledge fabric, data pipelines, and AI agents o Observability, automation, and integration layers · Understand how different enterprise systems connect and operate together · Work in innovation sprint-based environments with continuous feedback · Learn concepts like Self-healing systems, Predictive incident detection, Automated root cause analysis