$150,000–$200,000
Forward Deployed Engineer
Posted by Bretton AI · open on Gem as of
Pay not postedSan Francisco, CAFull-time
The Forward Deployed Engineer bridges Greenlite's AI capabilities and financial institutions' needs, delivering technical evaluations and production deployments in highly regulated banking environments.
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At a glance
Posted base pay
Not posted
Median $150K
Mid-level FDE postings105 postings · middle 50% of posted pay$122K–$162KThe work
Builds what the customer runs
Balance Mixed
Project stages
- Pre-sales
- Proof of concept
- Implementation
- Operations (not covered)
- Coding
- Configuration only
- Builds for
- External customers
- Level
- Mid
- Role
- Individual contributor
What they ask for
Experience
Background
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The job description from Bretton AI
Posted by Bretton AI on
About Greenlite
Greenlite builds AI agents for financial crime teams. Fintechs and banks use Greenlite agents to automate workflows like suspicious activity investigations, entity due diligence and regulatory reporting.
We're backed by Greylock and already have large banks and public companies using us in production every day. We're among the fastest growing enterprise AI companies in the world, and we're looking for pioneers who want to shape the future of AI in financial services.
The Role
As a Forward Deployed Engineer at Greenlite, you'll be the technical bridge between our AI capabilities and our customers' complex needs in highly regulated banking environments. The role combines deep technical expertise with strategic thinking to ensure our AI deployments drive real value while meeting stringent regulatory requirements.
You'll work directly with financial institutions to understand their workflows, demonstrate our technology, and guide technical implementation – all while helping shape our product roadmap based on customer insights.
What You'll Do
- Create and deliver compelling technical demonstrations that showcase Greenlite's capabilities to audiences ranging from compliance analysts to C-suite executives
- Design and implement proof-of-concept deployments that prove value while meeting strict banking security and compliance requirements
- Partner with our engineering team to solve technical challenges and influence our product roadmap based on customer needs
- Build reusable technical assets including demo environments, implementation guides, and best practice documentation
- Guide customers through technical evaluation, ensuring successful deployment of Greenlite's AI agents in production environments
- Identify and scope new use cases where Greenlite can solve additional customer problems, driving expansion opportunities
The Skillset You'll Bring
- 3+ years of experience in software engineering, technical pre-sales or solutions engineering, preferably in enterprise SaaS or fintech
- Strong technical background with hands-on experience in modern software development, API integration, and cloud architecture
- Experience working with AI/ML technologies and ability to explain complex technical concepts to various audiences
- Track record of successfully driving technical integrations with enterprise customers
- Exceptional communication and relationship-building skills with both technical and business stakeholders
Bonus points
- Previous experience working with financial institutions or in highly regulated environments
- Background in implementing AI/ML solutions in production environments
- Experience building internal tools or automation systems for financial services teams
Why Join Greenlite
- Be a founding member of our Deployments team, helping define our expansion strategy and processes
- Work at the intersection of AI agents and critical financial infrastructure
- Join a fast-growing, well-funded startup backed by top-tier investors
- Competitive compensation including significant equity ownership
- Medical, dental, and vision benefits
- Flexible PTO and work location policies
About Bretton AI
Bretton AI builds AI agents and AI-native operations for compliance, risk, fraud, and other back-office workflows at financial institutions.
Series B · 100–200 people
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