Forward Deployed AI Engineer

At HTEC, customers come to us with business problems they want to solve through AI: increasing revenue, reducing cost, transforming customer service, and modernizing how they build software or run operations. Your job is to turn these problems into robust AI solutions that deliver business value. 

As a Forward Deployed AI Engineer, you'll play a leading role in building and shipping AI solutions for our customers. That might mean designing custom AI applications, embedding AI across a customer's software development lifecycle, or building enterprise systems faster and differently with the new generation of AI tooling. Whichever shape the work takes, you'll own it from understanding the customer's need to deploying in their environment.  

What you'll do

Design and build what the customer needs: Depending on the engagement, you'll design and develop custom AI applications, embed AI across a customer's SDLC, or build enterprise systems using AI tools that change how software is made. In every case, you're shipping production-ready work that integrates with the customer's environment and scales with their use cases. 

Deliver solutions: Work across the full project lifecycle - understanding the requirements and system design and translating them into production grade solutions using AI tools for coding, testing, deployment, and support. 

Collaborate directly with customers: Partner with customer engineering teams to understand technical constraints, gather requirements, and problem-solve together. You'll join customer calls to discuss tradeoffs, progress, and technical feasibility. 

Work with world-class engineering teams: Collaborate with other HTEC engineers on projects, contributing your expertise and learning from others as you tackle complex AI challenges together. 

Shape our engineering culture: Help define how we build, how we learn, and how we work together as we scale our engineering team. 

What we're looking for 

Strong engineering fundamentals: You write exceptional code and deeply care about the craft. You have 5+ years of experience building elegant, production-ready software across multiple programming languages. 

Experience with Large Language Models: Track record building scalable applications with LLMs, using frameworks like LangChain, LlamaIndex, or similar tools. You understand the practical challenges of deploying AI in production. 

Proficiency with coding assistants: You are a builder and you know where and how to leverage AI tools like Claude Code, Codex, GitHub Copilot, Cursor and more. 

Problem-solving mindset: You love solving hard, new problems. You're comfortable in self-teaching, asking "why," and experimenting to tackle challenges you haven't seen before. 

Customer-facing skills: You can navigate customer conversations skillfully, understand their needs deeply, and translate those into technical solutions that actually work. 

Startup mentality: You jump in without instruction, embrace a "no job too big, no job too small" mindset, and want to contribute to building something exceptional. 

Collaborative approach: You're comfortable helping others and asking for help. You value integrity and want to build a culture of continuous learning. 

What to expect

In your first few months: You'll work on customer projects - building AI customer service agents, content moderation systems, intelligent automation - each project different from the last. With your second project, you'll have shipped LLM applications across more companies and use cases than most AI engineers. 

The opportunity: You'll have a front-row seat to how leading companies actually deploy AI solutions. You'll work across different industries, customers, and technical challenges, learning something new every day. 

The team: Work with senior engineers, who only want to work on high-impact projects. Collaborate closely with HTEC AI leadership. 

The environment: Engineering-first culture where technical excellence matters. We balance hacking things together for proofs-of-concept with building production-ready code that goes into customer environments. 

A typical day 

• You're the AI engineer for a customer project-maybe automating workflows with AI agents, building an intelligent search system, or an AI-enabled delivery pipeline 

• Dive into high-priority technical work-building an evals suite, testing different model configurations, implementing a new feature, or redesigning the delivery process 

• Join meetings with the customer's CTO to discuss technical tradeoffs, progress, and timeline 

• Heads-down coding time to push forward the current sprint 

• Maybe join a prospective customer call to share your perspective on what's technically feasible 

Important context

We balance quality and speed: We love rapid prototyping but our code goes into production in customer environments. You need to enjoy balancing elegance with expediency. 

Variety over predictability: You'll work across customers, programming languages, industries, and projects. You won't become an expert in the same product suite or serve the same user every day. This variety keeps things interesting but isn't for everyone. 

Customer proximity: You'll spend most of your time coding, but you'll be closer to customers than in most engineering roles. You'll interact with their engineering teams, understand their constraints, and ensure solutions fit their needs. 

Remote and In-person collaboration: Though we are a remote team, our team only thrives through collaboration and open communication. Our expectation from every team member is to embody this mindset. 

Our tech stack 

We're generally tech stack agnostic - we work in our customers' environments and codebases. Much of our work is in Python, but not exclusively. You'll become an expert at using various foundational models, building with tools like LangChain/LangSmith, and working with frameworks and tools for vector databases, evaluation, and monitoring. 

Our principles 

• Show, don’t only tell: Excellence is our standard, both in our code and in our language 

• Eat our own dogfood: We practice what we preach and use AI wherever possible 

• We are one team: Our people and relationships are our competitive advantage