Applied AI Engineer

We’re building the largest platform for tech professionals globally. We’re the only platform they need to stay ahead of tech trends and news, develop their careers and find opportunities at companies they believe in.
Our 1,800 customers include innovative companies of all sizes, from exciting startups to companies in the Fortune 100. This helps them hire the industry’s most sought-after professionals locally, nationally and remotely – ultimately contributing to the industry’s ability to innovate a better future.
What You’ll Be a Part Of Working at Built In is the chance to help shape a fast-growing company. With venture funding of $30 million to date, we’re expanding not just our geographic footprint but our products and technology. As a result, you’ll understand the impact of your work in a deeply personal, especially meaningful way.
We are looking for an Applied AI Engineer to design and build the autonomous systems that power Built In’s product suite. Our platform already generates deep analytical insights for customers—your job is to build the Agentic Action Layer that turns those insights into outcomes. You will create multi-agent systems that don’t just surface data but take intelligent, supervised action across the major AI frontiers: ChatGPT, Google Gemini, and Perplexity.
The ideal candidate has already shipped production agentic systems and knows where orchestration frameworks help versus where they get in the way. Design and implement production-grade agentic workflows—including Reflection, Self-Correction, Planning, and Multi-Agent Orchestration patterns—to power a growing portfolio of AI-driven product capabilities.
Operationalize Agents in Production:

Own the full lifecycle from rapid prototype to production deployment. Evolve Multi-Model Intelligence:

Develop systems that synthesize outputs from ChatGPT, Gemini, and Perplexity to identify sentiment discrepancies, detect brand hallucinations, and surface actionable intelligence for customers.
Build Scalable Cloud Infrastructure:

Design and maintain serverless backend services using Python and AWS Lambda, ensuring agents perform efficiently at scale with proper observability.
Drive Evaluation and Quality:

Build LLM-as-a-Judge evaluation frameworks, trace-based testing pipelines, and quality feedback loops that keep agent output reliable as models and prompts evolve.
Collaborate Across Teams:

Work closely with Software Engineers and Product Managers to integrate agentic behaviors into production frameworks, ensuring AI systems are stateful, observable, and resilient.
5+ years of full-time professional software engineering experience

. Internships, training programs and academic projects are valuable but dont count toward this.
~ Agentic systems youve shipped to production, for an employer or for customers

. Patterns like ReAct, Planning, Reflection, and Multi-Agent Orchestration. Youve moved agents from demo to production and dealt with the hard parts: failure handling, state management, and non-deterministic outputs.
~ Custom evaluation frameworks such as LLM-as-a-Judge, trace-based testing and regression suites, used to keep agent output quality up over time. You understand that the hardest part of production agents isnt building them. Hands-on work with frontier model APIs

from OpenAI, Google, Perplexity or Anthropic, including function calling, structured outputs, and streaming.

~ Strong Python

for AI orchestration.

Working knowledge of C# / .NET.

Our core platform runs on .NET, and youll integrate your agent systems with it, not just work alongside it.
Production experience with AWS serverless

(Lambda, Step Functions, EventBridge) for high-frequency, agentic workloads.
You use them to architect, refactor, test, and ship, not just autocomplete, and you can manage multiple agents across a codebase with minimal manual intervention.
What to Include in Your Application
We read every application for specifics. Please describe one or two agentic systems youve shipped:

Your role in building it.
Research shows that women and other marginalized groups tend to apply to roles only when they check every point on a job description. Qualified candidates are considered for employment without regard to race, religion, gender, gender identity, sexual orientation, national origin, age, military or veteran status, disability, or any other characteristic protected by applicable law.
Built In is guided by principles of diversity, equity and inclusion (DEI). Built In For The People, BuiltOut, United We Parent, Women United in Tech and Built In Tribe.
We have a dedicated Director, HR + Inclusion who oversees our DEI roadmap.
We are proud to be led by a woman CEO and founder, and that more than half of our managers and employees identify as women.
BUILT IN NEVER CONTACTS JOB APPLICANTS VIA TEXT, MESSENGER OR OTHER SIMILAR APPLICATIONS.