Forward Deployed Engineer

Location - Remote (US-Based Preferred — Strong Preference for Midwest or East Coast Time Zones)

Compensation - $125,000 – $200,000 Base + Variable Compensation + Competitive Equity

Visa - No New H-1B Sponsorship Available

Existing Work Authorization (H-1B Transfer or OPT) May Be Considered Case-by-Case

Company Stage - Seed Stage (~$13M+ Raised)

Industry - AI, Enterprise Software, AI Governance, Agentic AI, Financial Services

About the Company

The company is building a trust and governance platform for AI systems, helping enterprises safely deploy, monitor, and govern large language models, AI agents, and generative AI applications at scale.

Already deployed across major global enterprises and financial institutions, the platform enables organizations to implement AI guardrails, runtime controls, evaluation frameworks, and governance systems that ensure AI operates safely and reliably in production environments.

Founded by the former General Manager of IBM Watson and backed by leading venture investors, the company has rapidly emerged as a category leader in enterprise AI governance and was recently recognized as a Gartner Cool Vendor for Agentic AI.

With strong customer demand across banking, healthcare, retail, telecommunications, and consulting organizations, the company is rapidly expanding its customer-facing engineering team and hiring Forward Deployed Engineers to lead enterprise AI deployments.

This is a rare opportunity to work directly with Fortune 500 customers, own deployments from day one, and help shape how enterprises adopt AI responsibly at scale.

What You'll Do

• Own enterprise customer engagements from discovery through deployment
• Work directly with Fortune 500 clients to understand AI governance challenges and design technical solutions
• Deploy and configure AI runtime control systems, guardrails, evaluation frameworks, and governance workflows
• Build and customize LLM-powered applications, AI agents, and enterprise AI workflows
• Serve as the technical bridge between customers and internal engineering/product teams
• Lead proofs-of-concept and production deployments across multiple industries
• Translate ambiguous business requirements into scalable technical solutions
• Configure and deploy AI governance infrastructure within customer environments
• Create technical documentation, implementation plans, and deployment playbooks
• Surface customer feedback and product insights to internal teams
• Help customers successfully operationalize AI systems in production environments
• Become a trusted technical advisor for enterprise AI initiatives

Ideal Candidate Background

Experience Requirements

• 2–5 years of experience in Forward Deployed Engineering, Solutions Engineering, or Client-Facing Software Engineering
• Experience deploying AI/ML solutions into production customer environments
• Experience working directly with enterprise customers or external stakeholders
• Experience translating business requirements into technical implementations
• Experience working in startup or scale-up environments
• Experience supporting enterprise software deployments preferred
• Experience working with Fortune 500 customers preferred
• Experience in financial services, healthcare, consulting, or enterprise software preferred
• Demonstrated ability to operate independently in ambiguous environments

Technical Requirements

• Strong Python engineering skills
• Hands-on experience with AI/ML systems, LLMs, agents, or machine learning workflows
• Understanding of model capabilities, limitations, and trade-offs
• Experience deploying or supporting AI-powered applications
• Familiarity with cloud infrastructure concepts
• Familiarity with Kubernetes and containerized environments
• Understanding of AI evaluation, governance, guardrails, or monitoring concepts preferred
• Exposure to AWS, Terraform, Docker, or cloud-native tooling preferred
• Ability to troubleshoot technical issues in customer environments
• Strong problem-solving and systems thinking abilities

Education

• Bachelor's degree in Engineering, Computer Science, Data Science, or related technical field preferred
• Strong technical foundation with demonstrated engineering capabilities

Soft Skills

• Exceptional communication and interpersonal skills
• Comfortable presenting to technical and non-technical stakeholders
• Strong customer-facing presence
• Ability to simplify complex technical concepts
• High ownership mentality
• Comfortable operating in ambiguity
• Strong problem-solving mindset
• Consultative approach to customer engagement
• Startup mentality and bias toward action

Preferred Backgrounds

• Forward Deployed Engineering teams
• Solutions Engineering organizations
• Customer-facing AI engineering teams
• Enterprise AI startups
• AI governance and AI infrastructure companies
• Technical consulting organizations
• Financial technology companies
• Enterprise SaaS startups
• Early-stage venture-backed startups
• Engineers supporting Fortune 500 deployments

Compensation & Benefits

• Base Salary: $125,000 – $200,000
• Variable Compensation Package
• Competitive Equity Package
• Fully Remote Work Environment
• Direct Exposure to Fortune 500 Customers
• Significant Customer Ownership and Responsibility
• Opportunity to Become a Trusted Technical Advisor
• Direct Collaboration with Leadership Team
• Standard Benefits (Medical, Dental, Vision, 401k)
• Rapid Career Growth Opportunities
• Exposure to One of the Fastest-Growing Categories in Enterprise AI

Why Join

This is an opportunity to work at the center of enterprise AI adoption, helping some of the world's largest organizations deploy AI safely and responsibly.

You'll own customer engagements from discovery through deployment while working on real-world AI applications involving LLMs, AI agents, governance systems, and enterprise-scale AI infrastructure.

As one of the earliest Forward Deployed Engineers, you'll have outsized ownership, direct customer impact, and the opportunity to help define how enterprises operationalize AI during one of the most important platform shifts in technology.

Targeting Summary

The ideal candidate is a customer-facing technical engineer (target ~2–5 YOE) with experience deploying AI/ML solutions into enterprise environments.

This person should have strong Python fundamentals, hands-on exposure to LLMs or AI systems, and experience working directly with customers to solve technical problems.

The strongest candidates will come from Forward Deployed Engineering, Solutions Engineering, or client-facing software engineering backgrounds and demonstrate the ability to translate ambiguous business problems into successful technical implementations.