Forward Deployed Engineer

Mission

4Minds is an enterprise AI fine-tuning platform that transforms how organizations build and operate private, domain-specific AI. Unlike static systems, 4Minds’s AI platform learns continuously from live data in real time and can be deployed on-prem or your cloud provider.

Our patented technologies scale existing engineering teams and empower new AI teams, enabling rapid AI deployment, adaptation, and ROI. Through 4Minds’s automated data pipeline and proprietary knowledge graph, enterprises can connect all their data sources, including Microsoft, Databricks, AWS and Google, creating adaptive AI that surpasses the capabilities of conventional RAG-based systems.

Role Overview: Forward Deployed Engineer

As a Forward Deployed Engineer, you’ll operate at the intersection of engineering, AI, and live customer systems. You’ll work directly with enterprise clients to deploy, debug, and optimize 4Minds LLM training platform.

This is a hands-on, field-facing engineering role. You’ll move between writing code, diagnosing live issues, building integrations, tuning models, and translating operational insights into core product improvements.

Reporting to the CRO, you'll make an impact for us and our customers by solving hard, messy, high-stakes problems where AI meets real operations.

Key Responsibilities

• Partner directly with customers, from presales through onboarding and production, to ensure the 4Minds platform delivers new models for our clients.
• Debug, tune, and optimize real-time LLM development pipelines for clients.
• Build and maintain lightweight integrations, automations, and scripts connecting customer systems (TMS, CRMs, APIs) to our AI stack.
• Work closely with core engineering and product teams to reproduce, isolate, and resolve field issues rapidly.
• Develop deployment playbooks and reusable frameworks that make future rollouts faster and more reliable.
• Surface insights and edge cases from customer operations to inform model tuning, UX design, and roadmap priorities.
• Represent engineering in the field and communicate clearly with both technical and non-technical stakeholders.
• Ship quickly, iterate aggressively, and own every deployment like it’s your own product.

Required Qualifications

• BS in Computer Science, Engineer, or related technical field
• 3+ years in technical customer interfacing implementation role
• 5+ years in software engineering
• Strong experience with AI/LLM pipelines and open-source models including prompting, orchestration, or model tuning.
• Strong proficiency in Python, Node.js, or TypeScript
• Able to build integrations and debug live systems.
• Experience with real-time APIs, WebRTC, or streaming systems.
• Clear technical communication and ability to work directly with customer teams under time pressure.
• Comfort working in high-stakes, production environments where reliability and speed matter.
• Deep ownership mindset: you care about outcomes, not job titles.

Preferred Qualifications

• MS in Computer Science, Engineer, or related technical field
• Expertise in working with AI/LLM pipelines including prompting, orchestration, or model tuning.
• 5+ years in enterprise technical implementation roles
• 8+ years in software engineering
• Expert proficiency in Python, Node.js, or TypeScript
• Able to build integrations and debug live systems.
• Previous Enterprise experience implementing new technologies
• Passion and Desire to work with clients to deliver impact on their businesses

Compensation

• Base salary range: $190,000 - $225,000 annually
• Competitive equity package in venture-backed startup
• Performance-based bonus structure
• Annual merit-based salary reviews

Benefits

• Comprehensive medical, dental, and vision coverage (80% employer-paid)
• 401(k) plan
• Unlimited PTO policy with 15 days minimum
• 11 paid company holidays
• Flexible Spending Account (FSA) and Health Savings Account (HSA) options.

Professional Development

• Annual training and certification budget
• Access to online learning platforms
• Conference attendance opportunities
• Regular internal technical workshops and knowledge sharing sessions

Work Environment

• Remote Position with travel to Customer Sites 50% of the time
• Access to local co-working space
• High-performance workstations
• Modern office space in Dallas with standing desks and ergonomics equipment
• Monthly team events and learning sessions
• Collaborative in-office environment fostering innovation and teamwork

Process

We like to be efficient but do our due diligence. Here’s what you’ll expect from us:

• Interview with Recruiter (30-60 minutes)
• Interview with Hiring Manager (30 minutes)
• Technical Interviews and Presentation (Half day)
• Interview with CEO (45 Minutes)

Key skills/competency

• AI/LLM Pipelines
• Python/Node.js/TypeScript
• Customer Implementation
• Real-time Systems
• API Integration
• Debugging Live Systems
• Technical Communication
• Problem Solving
• Data Pipeline
• Machine Learning