Forward Deployed Engineer, GTM
At a glance
Mid-level Software Engineering role at Kong. Remote, United States · full-time · $125,370–$179,100 base.
techroles summary, based on the employer's posting.
What you'll do
- Build and launch AI agents for retention, pipeline growth, deal reviews, account research and sales preparation
- Connect language models with go-to-market systems, then test and refine prompts, retrieved context and model choices
- Monitor deployed agents for accuracy and performance problems, and correct output drift
- Work with analytics teams to link data sources for current customer and pipeline insights
- Create reusable prompt guides and training, while documenting agent design and meeting AI safeguards
What you bring
- At least five years of software engineering experience
- Practical knowledge of go-to-market strategy and AI operations, with LLM workflows or agents running in production
- Examples of AI tools or automations that changed real work, plus experience explaining technical ideas clearly
- A record of creating documentation or playbooks that others adopted and used at scale
Who this fits
This mid-level role suits a self-directed engineer who can work across teams, handle ambiguity and help go-to-market groups adopt AI tools. The position is listed as remote in Sacramento, United States.
From the employer
Are you ready to unlock intelligence?
If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others.
We are looking for a GTM Forward Deployed Engineer to build and launch AI agents for our go to market (GTM) teams (Marketing, Sales, Product and Revenue Operations) using platforms like Salesforce, Slack, Claude Code, Gemini, Snowflake, Marketo, Clay, Nooks, and Rox
Key Responsibilities:
Prototype and deploy AI agents for customer retention, pipeline generation, GTM productivity, deal inspection, account research, opportunity updates, and meeting prep.
Create prompt templates and system instructions for accurate, consistent outputs.
Define agent persona, tone, and fallback logic
Re-engineer GTM processes by connecting LLMs to GTM systems
Build and test agentic tools quickly.
Document agent logic and prompt structures to ensure scalable, independent automation across the global GTM organization.
Test system prompts, context retrieval, and model selection to boost output quality, seller adoption, and deal velocity.
Track and audit production agents to quickly fix output drift, performance gaps, and accuracy issues
Partner with GTM Analytics teams to integrate GTM data sources for real-time customer and pipeline insights.
Create practical prompt libraries, quick-reference playbooks, and training sessions to maximize seller, customer and/or potential customer value.
Ensure prompt, workflow, and deployed solutions meet security, legal, and company AI standards.
Required Qualifications:
Have 5+ years of software engineering experience
Working knowledge of GTM strategy, AI Operations and hands-on experience putting AI workflows or LLM agents into production.
Experience creating internal documentation, toolkits and playbooks that outlived your involvement and were adopted at scale.
Experience in a technical or cross-functional role that required problem-solving across teams and functions.
A track record of building AI-powered tools, automations, or workflows that changed how real work gets done — with specific examples you can speak to.
Clear, concise communication skills — you can explain a technical concept to someone who's never thought about it before, without talking down to them.
Comfort with ambiguity and self-direction; you don't need a detailed roadmap to know where to start.
Preferred Qualifications:
Hands-on experience with AI development platforms and tools such as Claude, Claude Code, MCPs, LLM APIs, custom agent frameworks, or workflow automation platforms.
Background in change management, organizational development, or a large-scale rollout that required bringing skeptical stakeholders along.
Experience in solutions engineering where you had to earn trust and deliver results quickly.
Familiarity with the enterprise SaaS tools Kong runs on: Okta, Slack, Google Workspace, Salesforce, Jira, or Freshservice.
Familiarity with Kong Konnect, Kong Gateway, or API management concepts — understanding how APIs and AI models connect will help you build smarter tools.
Experience helping others develop new technical skills, whether through formal training, one-on-one coaching, or team enablement programs
About Kong:
Kong Inc., the AI Connectivity Company, is building the connectivity layer of AI. Trusted by the Fortune 500® and AI-native startups alike, Kong’s unified API and AI platform enables organizations to secure, manage, accelerate, govern, and monetize the flow of intelligence across APIs and AI traffic — on any model, any cloud. For more information, visit www.konghq.com.