Forward Deployed Software Engineer

Recruiting From Scratch•San Francisco, NY

1d•Hybrid

About The Position

The company is building an AI-native enterprise platform that helps organizations modernize complex operational workflows across industries including construction, manufacturing, infrastructure, and government services. Its platform combines large language models, retrieval-augmented generation (RAG), production data pipelines, machine learning, and modern software engineering to deliver highly customized AI solutions directly inside customer environments. Engineers work closely with customers to rapidly build, deploy, and iterate on mission-critical software solving real-world operational problems. Founded by experienced operators with backgrounds at Palantir and backed by strong early customer traction, the company is rapidly scaling its engineering organization while maintaining a high engineering bar and an ownership-driven culture. Engineers own projects end-to-end—from customer discovery and backend architecture to AI workflows, frontend applications, and production deployment. As a Forward Deployed Software Engineer, you'll work directly with customers to design, build, and deploy AI-powered software tailored to their operational needs while collaborating closely with implementation, product, and engineering teams. This is a rare opportunity to join an early-stage AI company where every engineer directly shapes customer outcomes, product direction, and engineering culture while solving meaningful real-world problems across industries.

Requirements

1–5 years of experience as a Software Engineer building production applications
Experience building customer-facing software products
Experience working in structured engineering environments such as FAANG, Epic Systems, or similar organizations
Demonstrated experience working on cross-functional, entrepreneurial, or zero-to-one initiatives
Experience owning technical projects from concept through deployment
Strong software engineering fundamentals
Strong React development experience
Experience building production backend services and APIs
Hands-on experience with LLM orchestration and production AI applications
Deep understanding of Retrieval-Augmented Generation (RAG) architectures
Experience designing AI workflows using prompt engineering
Familiarity with production data pipelines and data integration
Comfortable contributing across frontend, backend, AI, and infrastructure systems
Strong debugging, testing, and software engineering best practices
Experience using AI coding tools and modern developer workflows
Bachelor's degree in Computer Science, Software Engineering, or related technical field required
Strong computer science fundamentals required
Strong product mindset
High ownership mentality
Excellent communication skills
Comfortable working directly with customers
Comfortable operating in ambiguity
Self-directed and proactive
Bias toward execution
Startup mentality
Low ego and highly collaborative
Entrepreneurial mindset

Nice To Haves

Experience collaborating directly with customers or business stakeholders preferred
Startup experience strongly preferred
Demonstrated ability to thrive in fast-paced, ambiguous environments
GPA above 3.5 strongly preferred (or strong explanation for lower GPA)
Palantir
Epic Systems
Meta
Early-stage AI startups
Enterprise AI startups
Applied AI companies
Manufacturing software companies
Construction technology companies
Industrial software companies
Forward Deployed Engineering organizations
Product engineering teams
Engineers building AI-powered enterprise products

Responsibilities

Own customer deployments from technical discovery through production rollout
Design and build production-grade data pipelines integrating disparate customer systems
Build AI-powered workflows leveraging LLMs, RAG, and prompt engineering
Design scalable backend services supporting customer-specific applications
Develop modern React applications tailored to customer workflows
Build and optimize AI evaluation pipelines for production use cases
Design APIs and backend architecture supporting enterprise deployments
Work closely with customers to understand business requirements and rapidly prototype solutions
Apply machine learning and data science techniques to unstructured enterprise data
Monitor production systems, improve reliability, and resolve mission-critical issues
Partner closely with Implementation Leads to deliver successful customer outcomes
Own end-to-end technical delivery across the full software stack