Applied AI Engineer, Advertising Agents
The Applied AI Engineer at Confidential Client will design and develop AI-driven systems to autonomously manage and optimize advertising accounts using advanced AI models such as LLMs and multimodal foundation models. This role focuses on building intelligent diagnosis and strategy recommendation models to improve advertiser performance and platform revenue, collaborating cross-functionally to enhance the platform's commercial competitiveness.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Engineering.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
About the Confidential Client
Confidential Client is a fast-growing engineering organization focused on content intelligence, recommendation systems, and adtech at internet scale. The team builds large-scale systems that connect advertisers with audiences using advanced machine learning and applied AI. This role will sit on an advertising/platform engineering team that leverages LLMs, multimodal models, and agentic systems to automate and optimize ad delivery.
About the Role
You will design, develop, and operate an AI-driven account hosting and optimization platform — the "AI Account Manager" — that autonomously diagnoses advertiser accounts, recommends safe, auditable tuning strategies, and executes optimizations to improve delivery and advertiser spend. Your work will directly reduce friction for advertisers, protect account health and compliance, and increase platform revenue.
Responsibilities
- Own algorithm and system design for the core AI Account Manager: automated hosting, autonomous optimization, and scheduling across many concurrent advertiser accounts.
- Build intelligent diagnosis and strategy-recommendation models that analyze performance data and delivery history to detect issues (e.g., scaling failures, sudden ROI drops, budget caps).
- Use LLMs and agent orchestration to generate actionable, auditable account-level tuning strategies and safely execute or simulate them.
- Implement long-running services with strong observability, dry-run safeguards, and offline/online evaluation to keep optimization quality measurable and prevent regressions.
- Collaborate closely with delivery-algorithm teams, product managers, and platform engineers to turn AI-account-management capabilities into measurable commercial improvements (retention, consumption).
Minimal Qualifications
- Bachelor's or Master's degree (or higher) in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Understanding of ad delivery platforms, recommendation systems, or related domains; entry-level candidates are welcome.
- Practical experience building, deploying, and optimizing agentic systems or large-model-based features in production.
- Strong software-engineering fundamentals: production-quality code, concurrent/asynchronous programming, typed/data-modeled code, and disciplined testing.
Core Technical Stack & Skills
- Hands-on experience with LLMs, retrieval-augmented generation (RAG), tool-use, memory handling, and agent orchestration.
- Experience producing structured/schema-validated LLM outputs and integrating with modern model APIs.
- Experience building reliable long-running services and REST/API integration; familiarity with Kubernetes or modern deployment tooling.
- Solid grounding in machine learning and AI fundamentals and familiarity with ad/recommendation system concepts.
- Excellent analytical and complex problem-solving abilities.
Preferred Qualifications
- 2+ years of algorithm experience in ad delivery or automated optimization, especially applying large-model capabilities to delivery/hosting/tuning workflows.
- Experience shipping commercial AI agents, instruction tuning of large models, or multimodal model integrations.
- Business acumen with digital-ad metrics (CPA, ROAS, CVR, CTR, conversions) and online A/B experimentation.
What We Offer
- Work with cutting-edge generative AI and agent technologies to reshape B2B ad monetization at internet scale.
- Direct commercial impact — your algorithms and systems will measurably influence advertiser growth and platform revenue.
- Access to top-tier foundation models, large-scale compute, and collaboration with experienced advertising, AI, and infra engineers.
Benefits
- Health, dental, and vision care (employee coverage details provided by the client).
- Top-tier 401(k) with company matching.
- Paid time off and paid holidays.
- FSA, HSA, and commuter benefits where applicable.
- Team activity budget and other employee programs.
Compensation (U.S. base salary range)
Annual Base Pay Range: $135,000 - $185,000 USD
Pay may vary based on job-related skills, level, experience, geographic location, and education. The role may also be eligible for discretionary bonus and equity/options per the client’s compensation program.
Location
This position is located in Mountain View, California (on-site / hybrid arrangements to be discussed with the recruiter).
Legal & Privacy Notes
California candidates: CPRA Privacy Notice and other state-specific disclosures will be provided as part of the application process.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
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