Senior Forward Deployed Engineer

Visvero, Inc.; Piscataway Township (NJ); On-site; USD 150,000 - 190,000; Full time

Job summary

Visvero, Inc. seeks a senior engineering lead to design, build and productionize agentic AI applications that integrate with enterprise systems.

You will own end-to-end delivery from problem framing to production, lead a small multi-disciplinary team, and ensure security, reliability and governance across Fabric/Azure environments.

Qualifications

• Proven experience building agentic or multi-agent AI systems that run in production and serve real users.
• Strong command of state management, concurrency, idempotency and authorisation for systems that act on a system of record on behalf of many users.
• Hands-on integration experience with enterprise APIs and data platforms, including designing safe read and write paths and handling failure gracefully.
• Working knowledge of modern AI application patterns — retrieval-augmented generation, prompt and context design, agent orchestration, tool use and protocols such as MCP.
• Strong, hands-on command of a major cloud platform, ideally Azure — able to independently provision, configure, deploy, secure and operate cloud resources, owning an application end to end rather than only consuming pre-built services.
• Demonstrated ability to prototype rapidly, using AI-assisted development and fast iteration to turn a loosely defined idea into something usable in days.
• The judgement and autonomy of a senior individual contributor — able to make sound architecture and feasibility calls alone, under time pressure, and explain them to non-technical stakeholders.

Responsibilities

• Design, build and harden agentic AI applications that read from and write to enterprise systems of record, grounded on Microsoft Fabric and Azure AI services.
• Embed with a Corporate Function team as the technical lead of a small, multi-functional pod — moving from problem, to prototype, to production at pace.
• Run a tight, iterative build cycle: align on the outcome, prototype, gather feedback, refine and finalise, typically within one to two weeks per loop.
• Own the quality of what you ship end to end — security, reliability, scalability, observability, and safe, governed write-back to source systems.
• Make the right build call for the problem: low-code and agent-builder platforms where they fit, custom code where they do not.
• Ensure the data behind each solution is AI-ready — modelled, governed and documented in Fabric, with lineage and access control that will stand up to audit.
• Set and document the reusable technical patterns, components and guardrails the team applies across every engagement.
• Become credible in a new business domain quickly, and challenge requirements constructively to land on the right solution rather than the requested one.

Skills

Agentic AI systems

State management

Concurrency

Authorization

Enterprise APIs

Tools

Azure

MCP

Job description

• Design, build and harden agentic AI applications that read from and write to enterprise systems of record, grounded on Microsoft Fabric and Azure AI services.
  
• Embed with a Corporate Function team as the technical lead of a small, multi-functional pod — moving from problem, to prototype, to production at pace.
  
• Run a tight, iterative build cycle: align on the outcome, prototype, gather feedback, refine and finalise, typically within one to two weeks per loop.
  
• Own the quality of what you ship end to end — security, reliability, scalability, observability, and safe, governed write-back to source systems.
  
• Make the right build call for the problem: low-code and agent-builder platforms where they fit, custom code where they do not.
  
• Ensure the data behind each solution is AI-ready — modelled, governed and documented in Fabric, with lineage and access control that will stand up to audit.
  
• Set and document the reusable technical patterns, components and guardrails the team applies across every engagement.
  
• Become credible in a new business domain quickly, and challenge requirements constructively to land on the right solution rather than the requested one.
  

Requirements

Required Qualifications

• Proven experience building agentic or multi-agent AI systems that run in production and serve real users — working systems, not demonstrations.
  
• Strong command of state management, concurrency, idempotency and authorisation for systems that act on a system of record on behalf of many users.
  
• Hands-on integration experience with enterprise APIs and data platforms, including designing safe read and write paths and handling failure gracefully.
  
• Working knowledge of modern AI application patterns — retrieval-augmented generation, prompt and context design, agent orchestration, tool use and protocols such as MCP.
  
• Strong, hands-on command of a major cloud platform, ideally Azure — able to independently provision, configure, deploy, secure and operate cloud resources, owning an application end to end rather than only consuming pre-built services.
  
• Demonstrated ability to prototype rapidly, using AI-assisted development and fast iteration to turn a loosely defined idea into something usable in days.
  
• The judgement and autonomy of a senior individual contributor — able to make sound architecture and feasibility calls alone, under time pressure, and explain them to non-technical stakeholders.