AI Engineer

About BrandBastion

BrandBastion is transforming the way the world’s leading brands manage conversations online. Our platform combines cutting-edge AI with human expertise to power social media management at scale—helping global brands like Netflix, Uber, Sephora, Red Bull, and The North Face turn engagement into brand growth. From moderation and crisis management to community engagement and analytics, we provide tons of features that ensure brands never miss a comment, opportunity, or insight.

What sets us apart? Unlike traditional social media tools where teams are stuck logging in and manually monitoring mentions, BrandBastion handles it for you—seamlessly and in real-time. If you’re excited about the intersection of AI, community, and brand storytelling—and want to be part of a team that’s redefining what social media management looks like—you’ll love it here. In this role, you will be reporting directly to our AI Lead.

About the role

We’re looking for an AI Engineer to take ownership of our classification agentic infrastructure—from enhancing and maintaining our existing systems to building entirely new AI-powered features. You will work with a full spectrum of social media interactions from some of the most widely recognized global brands to identify and act on threats to their reputation and opportunities for their business. The work spans from building base classification engines to implementing agentic workflows to handle complex client queries. All at a scale suitable for modern social media.

You’ll be instrumental in shaping how AI supports everything from moderation to customer support at BrandBastion. If you enjoy building at scale, love digging into data, and aren’t afraid to challenge the status quo, this role is for you.

What you'll do

• Design and Build : Develop new AI-enabled features and services that enhance classification accuracy and scalability.
• Maintain and Optimize : Continuously monitor, evaluate, and improve existing classification pipelines.
• Collaborate Across Teams : Work closely with product, data, and ops teams to ensure our AI systems are aligned with client needs and internal goals.
• Deploy with Confidence : Leverage AWS serverless services (Lambda, DynamoDB, S3, CloudWatch, etc.) to build scalable and cost-efficient solutions.
• Automate Monitoring : Implement systems that flag data drift, model degradation, and performance anomalies before they become client problems.
• Stay Current : Keep pace with developments in NLP, LLMs, and infrastructure best practices—suggest improvements proactively.
• Ensure Reliability : Set up tests, alerts, and fallbacks so our AI products are resilient and production-ready.

Requirements

Benefits