$200,000–$260,000
AI Field Engineer / Forward Deployed Engineer (FDE)
Published · Updated
$176,000–$228,000annualizedNew York, NY · San Mateo, CANew York, NY +1Remote
This hands-on forward deployed engineering role partners with AI-native customers to build and deploy AI applications, from POCs and MVPs through production.
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At a glance
Posted base pay
$176K–$228KAbove the median
Median $190K
This job$176K–$228KTypical senior FDE payMiddle 50% of 1,789 postings$160K–$220KThe work
Builds what the customer runs
Balance
- Mostly building
- Mixed
- Mostly pre-sales or support
Project stages
- Pre-sales (not covered)
- Proof of concept
- Implementation
- Operations
- Coding
- Writes production code
- Builds for
- External customers
- Level
- Senior
- Role
- Individual contributor
What they ask for
Experience
Background
Tools
Visa
Less common in FDE jobs
- Fully remote28%
- Sponsors visas28%
- Covers proofs of concept40%
- Individual contributor or manager: Individual contributor49%
Share of US FDE postings that state each fact.
The job description from abdulrauf1-1741255834
Posted by abdulrauf1-1741255834 on
Location: New York, NY / San Mateo, CA / Remote, USA
Employment Type: Full-time
Experience: 3–10 years
Compensation: $176K–$228K base | $220K–$285K OTE + meaningful equity
Visa: H-1B transfers and TN visas sponsored; O-1 considered case-by-case
About the Role
We’re hiring an AI Field Engineer / Forward Deployed Engineer (FDE) to join our AI’s high-velocity team
You’ll work directly with ambitious AI-native companies to turn complex AI challenges into production-ready systems. This is a highly hands-on role sitting at the intersection of AI engineering, product, and customer delivery.
You’ll build POCs, MVPs, and production integrations while working directly with customers, account executives, and engineering teams. You’ll also engage with technical and executive stakeholders to discuss architecture, strategy, and business outcomes.
This is not a traditional consulting or solutions role you’ll be hands-on-keyboard, writing code, deploying systems, solving technical problems, and contributing directly to our products and platform.
What You’ll Do
- Work directly with customers to understand their technical and business challenges.
- Design and build POCs, MVPs, and production AI applications.
- Deploy and optimize LLM and generative AI workloads in production.
- Work with open-source models, inference infrastructure, and AI/ML platforms.
- Collaborate with customer engineering teams, account executives, and Fireworks product/engineering teams.
- Translate customer requirements into scalable technical solutions.
- Troubleshoot complex AI, infrastructure, and deployment challenges.
- Communicate technical architecture and tradeoffs to both engineers and executive stakeholders.
- Contribute code and product improvements directly to the codebase.
- Turn customer learnings into product feedback and help shape our roadmap.
- Take ownership of projects from initial discovery through production deployment.
What We’re Looking For
We’re looking for engineers who combine strong technical depth with excellent customer-facing skills.
You may come from backgrounds such as:
- Forward Deployed Engineer
- AI/ML Engineer
- Applied AI Engineer
- AI Solutions Engineer
- Solutions Architect
- Sales Engineer
- Customer Engineer
- ML/AI Infrastructure Engineer
- Customer Success Engineer with strong technical depth
Required
- 3–10 years of experience in a client-facing technical or AI/ML engineering role.
- Strong Python programming skills.
- Experience building and deploying AI/ML or generative AI applications.
- Experience working with LLMs and/or open-source AI models.
- Ability to work directly with customers and communicate technical concepts clearly.
- Experience building POCs and taking solutions toward production.
- Strong problem-solving skills and the ability to operate effectively in ambiguous environments.
- Willingness to work hands-on across engineering, customer delivery, and product.
Technical Experience
Experience with some of the following is highly relevant:
- Python
- vLLM
- SGLang
- TensorRT-LLM
- Kubernetes
- AWS, Azure, or GCP
- AWS Bedrock / SageMaker
- Azure AI Foundry
- GCP Vertex AI
- LLM fine-tuning, including SFT, DPO, or RFT
- GPU infrastructure
- Model inference and optimization
You do not need experience with every technology listed, but you should have strong fundamentals in AI/ML engineering and be comfortable learning quickly.
Why Join?
- Work directly with cutting-edge AI companies.
- Build real AI systems that move from prototype to production.
- Work across engineering, product, and customer delivery.
- Contribute directly to an AI infrastructure platform.
- Join a highly technical, builder-first team.
- Competitive compensation of $220K–$285K OTE + meaningful equity.
- US visa support including H-1B transfers and TN visas.
View posting at abdulrauf1-1741255834
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