Introducing the Agent Engineer: Where AI meets real-world impact
June 6, 2025
Written by Amy Jin
Generative AI has opened up extraordinary new capabilities, but turning those capabilities into systems that drive business outcomes requires more than just powerful models. It takes a new kind of builder—someone who can navigate advanced LLMs, understand real-world workflows, and create intelligent agents that actually deliver value.
At Decagon, we call this role the Agent Engineer.
Agent Engineers are at the forefront of some of the most exciting work happening in AI today. They operate at the intersection of engineering, product, and go-to-market, building and deploying agentic systems that bridge the gap between what LLMs can do and what businesses need.
This role is foundational to how we operate at Decagon. In this post, we’ll unpack what Agent Engineers actually do and offer a glimpse into the deeply cross-functional and impactful work that defines this next generation of AI-native builders.
What is an Agent Engineer?
Agent Engineers are deeply technical and product-minded contributors who take full ownership of designing, building, and deploying AI agents. They build agents that interact with live customer data, make decisions on behalf of users, and operate in complex, high-stakes environments.
Agent Engineers span the full lifecycle of AI development and productization:
- Scoping and discovery: Embed directly with customers understand complex human workflows and translate them into clear agent behaviors that drive high-leverage automation opportunities
- Rapid prototyping and building: Craft end-to-end agentic systems and workflows using LLMs, APIs, and Decagon’s conversational AI platform
- Prompt and behavior design: Creatively implement prompt chains, tools, routing logic, and safe fallbacks
- Iterating in production: Stress-test and deploy agents in live environments, observing usage and refining behavior based on real-world feedback
- Collaborating across disciplines: Partner with agent product managers, designers, and platform teams to ensure agents are performant, safe, and aligned with business goals
In short, Agent Engineers bridge the gap between smart AI models and their real-world impact.
Why AI agents fail without Agent Engineers
AI agents are poised to transform every industry, but most don’t work out of the box. Despite powerful models and mature infrastructure, turning LLMs into reliable, task-completing systems still takes orchestration, abstraction, and relentless iteration. LLMs are generalists; business workflows require specialists. Agent Engineers bridge that gap.
Here’s just a few examples of that work in the field:
- Curology: a single Agent Engineer replaced dozens of manual repetitive workflows with an AI agent that now autonomously handles subscription management and shipment inquiries while providing a seamless customer experience.
- Bilt: our team built AI agents to manage complex financial services inquiries, driving a 70% resolution rate while upholding rigorous compliance and security protocols.
- Noom: an Agent Engineer streamlined the customer’s entire support infrastructure with AI agents, boosting deflection from 59% to 68% in just 30 days.
Agent Engineers are at the forefront of deploying and optimizing these agents, shipping intelligent workflows that automate complex business processes and deliver measurable ROI for our customers. You can explore more of our case studies here!
Who makes a great Agent Engineer?
We’ve found that exceptional Agent Engineers tend to share a few key traits:
- Technical depth with a product mindset: They can write production-grade code but are also obsessed with solving real problems for users, possessing a strong ability to think in edge cases, failure modes, and user expectations.
- Comfort with ambiguity: Every customer presents unique problems. One week they’re building a retention policy agent, the next they’re ideating on a content moderation system. They don’t need a fully defined spec to start building and are excited to explore, tinker, and learn in the field.
- Strong collaboration skills: They enjoy working directly with customers and communicate clearly with stakeholders across engineering, product, and design, effectively bringing cross-functional teams together.
- Builder’s instinct: They take pride in building systems that people actually use and are energized by fast feedback loops with direct, quantifiable results. They aren’t afraid to own outcomes in high-context, high-impact environments.
This role attracts technical generalists who may have explored product roles or founded companies, but ultimately feel most at home building real solutions for real users.
Why now—and why at Decagon?
We’re at an inflection point in AI: intelligent agents are moving from experimental prototypes to real-world products, with the potential to transform how we interact with software. This is a rare chance to help shape that transformation from the ground up—designing not just the technology, but the very foundation of how these agents work across tools, teams, and data.
At Decagon, we’re building the systems and infrastructure that make this shift possible. It’s not just a technical challenge, but also an opportunity to influence the trajectory of a fast-moving company and help define an emerging category.
As we expand our presence in San Francisco and New York City, we’re looking for exceptional engineers who are excited about this unique intersection of AI and customer impact.
Join us
There are very few places where you can prototype with frontier LLMs, ship to production in days, and watch users engage with the systems you built—all while owning the entire stack, from intent parsing and tool usage to API integration and observability. This role at Decagon is one of those places.
From my own experience working across both agent development and broader engineering initiatives at Decagon, I’ve seen firsthand how uniquely impactful this work can be. Whether I’m building intelligent workflows for customers or designing infrastructure that supports our agent platform, it’s rare to find an environment where the work transitions from concept to production within days, actively powering user experiences and transforming how businesses operate.
If you’re looking for a role where you can:
- Build at the frontier of LLMs, automation, and user interaction
- Deploy AI agents that solve high-value business use cases across industries including retail, travel and hospitality, fintech, edtech, and more
- Work directly with customers on high-impact use cases
- Ship fast, iterate constantly, and own your work from idea to production
- Join a fast-moving, collaborative team solving real-world challenges with AI
We’d love to hear from you!
Introducing the Agent Engineer: Where AI meets real-world impact
Agent Engineers navigate advanced LLMs, understand real-world workflows, and create intelligent agents that actually deliver value.
Generative AI has opened up extraordinary new capabilities, but turning those capabilities into systems that drive business outcomes requires more than just powerful models. It takes a new kind of builder—someone who can navigate advanced LLMs, understand real-world workflows, and create intelligent agents that actually deliver value.
At Decagon, we call this role the Agent Engineer.
Agent Engineers are at the forefront of some of the most exciting work happening in AI today. They operate at the intersection of engineering, product, and go-to-market, building and deploying agentic systems that bridge the gap between what LLMs can do and what businesses need.
This role is foundational to how we operate at Decagon. In this post, we’ll unpack what Agent Engineers actually do and offer a glimpse into the deeply cross-functional and impactful work that defines this next generation of AI-native builders.
What is an Agent Engineer?
Agent Engineers are deeply technical and product-minded contributors who take full ownership of designing, building, and deploying AI agents. They build agents that interact with live customer data, make decisions on behalf of users, and operate in complex, high-stakes environments.
Agent Engineers span the full lifecycle of AI development and productization:
- Scoping and discovery: Embed directly with customers understand complex human workflows and translate them into clear agent behaviors that drive high-leverage automation opportunities
- Rapid prototyping and building: Craft end-to-end agentic systems and workflows using LLMs, APIs, and Decagon’s conversational AI platform
- Prompt and behavior design: Creatively implement prompt chains, tools, routing logic, and safe fallbacks
- Iterating in production: Stress-test and deploy agents in live environments, observing usage and refining behavior based on real-world feedback
- Collaborating across disciplines: Partner with agent product managers, designers, and platform teams to ensure agents are performant, safe, and aligned with business goals
In short, Agent Engineers bridge the gap between smart AI models and their real-world impact.
Why AI agents fail without Agent Engineers
AI agents are poised to transform every industry, but most don’t work out of the box. Despite powerful models and mature infrastructure, turning LLMs into reliable, task-completing systems still takes orchestration, abstraction, and relentless iteration. LLMs are generalists; business workflows require specialists. Agent Engineers bridge that gap.
Here’s just a few examples of that work in the field:
- Curology: a single Agent Engineer replaced dozens of manual repetitive workflows with an AI agent that now autonomously handles subscription management and shipment inquiries while providing a seamless customer experience.
- Bilt: our team built AI agents to manage complex financial services inquiries, driving a 70% resolution rate while upholding rigorous compliance and security protocols.
- Noom: an Agent Engineer streamlined the customer’s entire support infrastructure with AI agents, boosting deflection from 59% to 68% in just 30 days.
Agent Engineers are at the forefront of deploying and optimizing these agents, shipping intelligent workflows that automate complex business processes and deliver measurable ROI for our customers. You can explore more of our case studies here!
Who makes a great Agent Engineer?
We’ve found that exceptional Agent Engineers tend to share a few key traits:
- Technical depth with a product mindset: They can write production-grade code but are also obsessed with solving real problems for users, possessing a strong ability to think in edge cases, failure modes, and user expectations.
- Comfort with ambiguity: Every customer presents unique problems. One week they’re building a retention policy agent, the next they’re ideating on a content moderation system. They don’t need a fully defined spec to start building and are excited to explore, tinker, and learn in the field.
- Strong collaboration skills: They enjoy working directly with customers and communicate clearly with stakeholders across engineering, product, and design, effectively bringing cross-functional teams together.
- Builder’s instinct: They take pride in building systems that people actually use and are energized by fast feedback loops with direct, quantifiable results. They aren’t afraid to own outcomes in high-context, high-impact environments.
This role attracts technical generalists who may have explored product roles or founded companies, but ultimately feel most at home building real solutions for real users.
Why now—and why at Decagon?
We’re at an inflection point in AI: intelligent agents are moving from experimental prototypes to real-world products, with the potential to transform how we interact with software. This is a rare chance to help shape that transformation from the ground up—designing not just the technology, but the very foundation of how these agents work across tools, teams, and data.
At Decagon, we’re building the systems and infrastructure that make this shift possible. It’s not just a technical challenge, but also an opportunity to influence the trajectory of a fast-moving company and help define an emerging category.
As we expand our presence in San Francisco and New York City, we’re looking for exceptional engineers who are excited about this unique intersection of AI and customer impact.
Join us
There are very few places where you can prototype with frontier LLMs, ship to production in days, and watch users engage with the systems you built—all while owning the entire stack, from intent parsing and tool usage to API integration and observability. This role at Decagon is one of those places.
From my own experience working across both agent development and broader engineering initiatives at Decagon, I’ve seen firsthand how uniquely impactful this work can be. Whether I’m building intelligent workflows for customers or designing infrastructure that supports our agent platform, it’s rare to find an environment where the work transitions from concept to production within days, actively powering user experiences and transforming how businesses operate.
If you’re looking for a role where you can:
- Build at the frontier of LLMs, automation, and user interaction
- Deploy AI agents that solve high-value business use cases across industries including retail, travel and hospitality, fintech, edtech, and more
- Work directly with customers on high-impact use cases
- Ship fast, iterate constantly, and own your work from idea to production
- Join a fast-moving, collaborative team solving real-world challenges with AI
We’d love to hear from you!
Download the webinar
The future of customer experience starts here.
