About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
About the Role
Appier is seeking a Software Engineer, Ad Serving to be the deepest technical problem-solver behind our advertising products. When a campaign underdelivers, when CVR drops without an obvious cause, or when a partner integration behaves unexpectedly, you are the person who reproduces the issue, reads the logs, queries the data, and gets to the actual root cause — then explains it in language a client or an account team can act on.
You will work at the intersection of ad serving, data, and machine learning: diagnosing delivery and performance issues across the full funnel from bid request to conversion, validating partner and supply integrations, and turning what you find into concrete improvements to our bidding and supply strategy. You will also build the tooling and playbooks that let the rest of the organization resolve these issues without you.
[The seniority/title is determined by job-related skills, experience, and evaluation after the interview.]
Responsibilities
- Own Tier 2/3 technical escalations across ad serving, tracking, data pipelines and ML-driven bidding, triaging and resolving complex issues that frontline teams cannot.
- Perform structured Root Cause Analysis (RCA) on production issues — including campaign delivery failures, budget pacing anomalies, fill rate degradation, and CTR / CVR / CPA / ROAS fluctuations — and communicate findings clearly to both engineering and commercial stakeholders.
- Reproduce and resolve technical issues across OpenRTB integrations, VAST / video playback, SDK-based environments, MMP postbacks, and conversion tracking (S2S, CAPI, SKAdNetwork / Privacy Sandbox).
- Query and analyze large-scale bid, impression, click and conversion datasets with SQL to isolate anomalies, quantify impact, and separate measurement problems from genuine performance problems.
- Analyze supply-side data to strengthen delivery strategy: reconstruct supply paths from the SupplyChain object, cross-check against publisher ads.txt / app-ads.txt and exchange sellers.json, measure placement-level quality and bid duplication, and surface invalid traffic and Made-for-Advertising signals — translating findings into supply path, placement-level bidding and exclusion-list recommendations.
- Build internal tooling, scripts and automated diagnostics that shorten investigation time, and maintain troubleshooting playbooks and runbooks that enable frontline teams to self-resolve a growing share of issues.
- Validate new advertiser, publisher and partner integrations end to end before launch, proactively identifying misconfigurations in tracking, deal setup and traffic routing.
- Partner with Product, Engineering and Data Science to turn recurring issues into product and platform improvements, and to influence prioritization with evidence from real cases.
- Define and track operational quality metrics such as mean time to resolution, escalation rate and issue recurrence rate.
About You
[Minimum qualifications]
- Minimum 3 years of hands-on experience in technical support, solutions engineering, ad operations or a similar technical client-facing role, including at least 2 years working with ad tech systems (DSP, SSP, ad server, ad network or MMP).
- Solid understanding of the programmatic advertising ecosystem: the real-time bidding flow, auction types, budget pacing, frequency capping, attribution models and attribution windows, tracking pixels and tags, and viewability.
- Strong SQL skills — able to write complex queries from scratch, join event-level datasets correctly, and reason about how a mis-specified join distorts a metric.
- Proficiency in at least one scripting or general-purpose programming language (e.g., Python) to automate investigation, parse large log files and build internal utilities.
- Demonstrated troubleshooting ability with logs, APIs and distributed systems — including REST API debugging, HTTP request/response inspection and log analysis.
- Excellent diagnostic instincts: when a metric moves, you can lay out a structured order of investigation instead of trying fixes at random.
- Experience with AI-assisted development tools such as GitHub Copilot, Cursor, and Windsurf to enhance coding efficiency, streamline debugging, and facilitate code refactoring. Familiarity with these tools is essential to our workflow.
- Strong communication skills — able to explain a technical root cause to a non-technical client or account team, and to write an incident summary that stands on its own.
- Fluent English communication skills, both verbal and written.
[Preferred qualifications]
- Hands-on experience reading and debugging OpenRTB bid requests and responses at the field level (e.g., imp.*, source.schain, user.eids, imp.ext.gpid, imp.bidfloor, app.bundle).
- Experience working with log-level or event-level advertising data at scale (e.g., BigQuery, Spark, Snowflake, ClickHouse) and with query performance optimization on large partitioned tables.
- Familiarity with supply chain transparency standards — ads.txt / app-ads.txt, sellers.json, SupplyChain Object — and with supply quality concepts such as invalid traffic (IVT / SIVT), domain and bundle spoofing, ad stacking and Made-for-Advertising inventory.
- Experience with mobile measurement partners (AppsFlyer, Adjust, Branch), postback debugging, and privacy-preserving measurement frameworks (SKAdNetwork, AdAttributionKit, Privacy Sandbox).
- Familiarity with VAST / video ad serving, Open Measurement SDK, and CTV / in-app environments.
- Experience with monitoring and observability tools (e.g., Datadog, Grafana, Kibana, Prometheus) and with incident response processes.
- Understanding of auction dynamics such as first-price auctions, bid shading, floor pricing and supply path optimization.
- Exposure to A/B testing, holdout design or incrementality measurement.
- Additional language ability for regional client support (e.g., Mandarin, Japanese, Korean).
Open to overseas candidates/Visa Support
This position is open to based in Taipei, Taiwan or Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.
