Applied AI Engineer, Advertising Agents

Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech.

Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale.

Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence.

If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about

Are you looking to engage in AI Account Management algorithm work as an excellent engineer to join our advertising team? In this role, you will be responsible for designing, developing, and optimizing an AI-driven intelligent account hosting and optimization platform. You will utilize LLMs, Multimodal Foundation Models, and related techniques to build AI advertising expert systems (AI Agents) that run a closed optimization loop — autonomously diagnosing accounts and safely auto-tuning delivery.

Your work will directly lower the delivery barrier for global advertisers on our platform. While ensuring the health and compliance of the account ecosystem, your intelligent operations will maximize advertisers' willingness to spend and platform revenue.

• →Build In-house AI Account Manager System: Own the algorithm and system design for the core "AI Account Manager" — realizing automated hosting, autonomous optimization, and intelligent scheduling of optimization across many advertiser accounts running concurrently.
• →Construct Intelligent Diagnosis and Strategy Recommendation Models: Analyze advertisers' performance data and delivery history to assess account health and automatically diagnose delivery pain points (such as inability to scale volume, sudden drops in ROI, or budget capping), then use LLMs to generate and safely execute actionable, auditable account-level tuning strategies.
• →Ensure Reliability and Measurable Quality: Build the long-running services, observability, dry-run safeguards, and offline/online evaluation that keep optimization quality measurable and catch regressions before they reach live spend.
• →Cross-team Collaboration to Drive Growth: Work closely with the platform-side ad delivery algorithm team and product managers to transform AI account management capabilities into the platform's core commercial competitiveness, improving advertiser retention rate and overall consumption.

• Education Background: Bachelor's/Master's degree or higher in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Work Experience:
• Possess a basic understanding of fields such as ad delivery platforms or recommendation systems; fresh graduates are acceptable.
• Familiar with building, deploying, and optimizing agentic systems in production environments.
• Strong software-engineering fundamentals: production-quality code, asynchronous/concurrent programming, typed and data-modeled code, and a solid testing discipline.
• Core Technical Stack:
• Master LLMs, RAG, tool-use, memory handling, and agent orchestration (including MCP-style tool ecosystems).
• Hands-on with harness engineering, structured/schema-validated LLM outputs, and integration with modern model APIs.
• Experience with REST/API integration and building reliable long-running services; familiar with modern deployment tools such as Kubernetes.
• Solid grounding in machine learning and AI fundamentals; familiar with advertising or recommendation system concepts.
• Possess excellent analytical and complex problem-solving abilities.

• Industry Background: Algorithm experience in the field of ad delivery, with more than 2 years applying large-model capabilities to systems such as automated delivery, automated hosting, autonomous tuning, or automatic scheduling.
• AI Production Experience: Experience landing commercial AI agents (agent-based systems), large-model instruction tuning, or multimodal models.
• Business Acumen: Understanding of digital advertising mechanics and core metrics (CPA, ROAS, CVR, CTR, conversions) and of online A/B experimentation.