About Starbridge

Starbridge helps go-to-market teams win in the public sector. Government buyers signal their priorities constantly, in council meetings, budget documents, RFPs, and public records, but that intelligence is scattered across thousands of sources and impossible to track by hand. Our platform surfaces those signals, connects them to the right buyers, and turns them into pipeline.

We move fast, stay close to our customers, and are building the category. This is a chance to join early and shape how we scale.

About the role

We’re looking for an AI Engineer to help us build and scale the next generation of AI-powered systems at Starbridge. You’ll work on projects that sit at the core of our product—building, evaluating, and deploying LLM-driven features that make it easier for organizations to access, understand, and act on complex public data.

You’ll collaborate closely with our engineering and product teams to design new AI capabilities, such as deep document analysis and interactive chat experiences. This role combines hands-on software engineering, applied machine learning, and product experimentation, with the goal of delivering reliable, high-performing AI systems to production.

You’ll have the opportunity to work with models from OpenAI, Anthropic, and Gemini, contribute to our AI infrastructure, and play a key role in shaping how we leverage generative AI across our platform.

Your responsibilities

• Collaborate closely with our team as we productize new AI-powered capabilities: such as AI proposal writing & search experiences.

• Evaluate and monitor the performance of AI models (we will work with models from OpenAI, Anthropic, Gemini, Parallel.ai) & systems through rigorous testing and experimentation.

• Stay up-to-date with the latest advancements in AI and machine learning research, and proactively suggest improvements to enhance our generative AI capabilities.

• Implement strong testing and CI/CD practices that help us move with confidence in our AI system development

Is this you?

• Bachelor’s degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience

• Have experience working in a startup or a smaller company with real engineering impact.

• 5+ years of professional experience in software engineering, AI/ML development including:

  • Proficiency with production software (Python) and systems design

  • Machine learning algorithms and model development techniques

  • ML lifecycle tools like MLflow, dvc, weights & biases

  • Cloud deployment of ML systems

  • Professional experience with LLMs and large-scale models

• Very strong software engineering skills with a track record of building scalable, distributed product machine learning systems

• Product thinking: ability to take product requirements and strategize how to apply LLMs

• Ability to communicate complex ideas and concepts effectively

Bonus if you have:

• Experience building scalable applications with LLMs, using frameworks such as LangGraph, LiteLLM, Agent Client Protocol, and Koog

• Depth of knowledge with RAG implementation and improvements

• Proficiency with Kotlin

Interview Process

We move fast — really fast. Getting back to someone today beats tomorrow, and our interview process reflects that mindset. Please keep us posted on your timeline so we can move quickly and speed things up where needed. All interviews are conducted via Google Meet.

How We Work

• Build Bridges to Help Customers Win - We pride ourselves on being obsessively customer-centric.

• Shooting Star Speed - We move with extreme speed. We value momentum, decisiveness, and the ability to accelerate when it matters.

• Fun Is a Feature - Fun is a Feature means we intentionally design Starbridge to be an energizing place to do hard work. Joy, humor, and camaraderie make great teams faster, sharper, and more resilient.

• In the Arena - We believe the best ideas come from living close to the work, feeling the friction, hearing the nuance, and experiencing the details firsthand.

Benefits include:

• Competitive salary + early-stage equity

• Unlimited PTO

• Regular offsites (NYC + global locations)