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Forward Deployed Engineer

Updated

Pay not postedUSRemote

Forward Deploy Engineers deploy and adapt Hermes Agent Enterprise in complex cloud, on-premises, and hybrid customer environments.

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View posting at Nous Research

At a glance

Posted base pay

Not posted

The work

Builds what the customer runs

Balance

  1. Mostly building
  2. Mixed
  3. Mostly pre-sales or support

Project stages

  1. Pre-sales (not covered)
  2. Proof of concept (not covered)
  3. Implementation
  4. Operations
Coding
Writes production code
Builds for
External customers
Level
Senior
Role
Individual contributor

What they ask for

Experience

  • 5+ yearssoftware engineering or solutions engineering experience building and deploying production systems

Background

  • Software engineering
  • Solutions and customer engineering

Tools

  • Hermes Agent Enterprise
  • Docker
  • Kubernetes
  • LLMs
  • AI agents
  • RAG systems
  • model orchestration frameworks
  • enterprise APIs

Less common in FDE jobs

  • Fully remote26%
  • Individual contributor or manager: Individual contributor45%

Share of US FDE postings that state each fact.

The job description from Nous Research

Posted by Nous Research on

The Role

As a Forward Deployed Engineer at Nous Research, you'll deploy and adapt Hermes Agent Enterprise inside complex customer environments. You'll partner directly with enterprise customers to understand their workflows, integrate internal systems, and deliver production-ready AI solutions that solve real business problems.

You'll work across engineering, infrastructure, and customer teams to bridge the gap between cutting-edge AI research and reliable enterprise deployments. This is an ideal role for someone who enjoys solving ambiguous technical challenges, working closely with customers, and shipping high-impact solutions.

Responsibilities

  • Deploy Hermes Agent Enterprise across cloud, on-premises, and hybrid customer environments.
  • Integrate enterprise APIs, internal data sources, authentication systems, and business applications into agent workflows.
  • Partner directly with customers to scope requirements, implement solutions, and iterate based on feedback.
  • Debug and resolve production issues across infrastructure, orchestration, integrations, and AI application layers.
  • Build reusable deployment patterns, tooling, and best practices that improve implementation speed and reliability.
  • Collaborate with engineering and research teams to influence product direction based on customer needs.
  • Improve deployment observability, monitoring, and operational tooling to support production AI systems.
  • Document deployment architectures, integration guides, and customer implementation patterns.

Qualifications

  • 5+ years of software engineering or solutions engineering experience building and deploying production systems.
  • Experience working directly with enterprise customers or cross-functional stakeholders to deliver technical solutions.
  • Strong debugging skills across distributed systems, backend services, and cloud infrastructure.
  • Comfortable working across backend engineering, infrastructure, APIs, and AI application layers.
  • Excellent communication skills with the ability to translate complex technical concepts into practical customer solutions.
  • Entrepreneurial mindset with the ability to thrive in fast-moving, ambiguous environments.

Nice-to-Have

  • Experience with Docker, Kubernetes, and modern cloud infrastructure.
  • Familiarity with LLMs, AI agents, RAG systems, or model orchestration frameworks.
  • Experience integrating enterprise systems such as CRMs, data warehouses, internal APIs, or identity providers.
  • History of shipping customer-facing technical solutions in enterprise or infrastructure-focused environments.

View posting at Nous Research

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Pay and conditions

Posted pay
Pay not posted
Location
US
Work arrangement
Remote
Remote work restrictions
Americas (US time zones)
Employment type
Full-time
Experience requirements
  • 5+ years: software engineering or solutions engineering experience building and deploying production systems (required)