AdTech systems I've worked on, debugged and optimized.
Structured engineering case studies demonstrating real-world problem discovery, data pipeline architecture, diagnostic troubleshooting, and operational root-cause analysis (RCA) across programmatic bidding, ad serving, video streaming, and APIs.
Programmatic buyers and SSPs silently drop bid requests due to subtle JSON schema violations (such as missing poddur in CTV pods, invalid ext.eids, or unencoded GDPR user.ext.consent strings), contributing to lost bid opportunities and unfilled inventory.
🎯 2. Context & Stakeholders
SSPs, DSPs, Programmatic Publishers, and Integration Engineers.
Built an interactive, in-browser validation engine that evaluates real-time bid requests and responses against IAB specifications. Features 1-click test payloads (Display Banner, CTV Pod, Cookieless EIDs, Invalid Payload) and an instant clipboard export tool formatted for Jira and Slack tickets.
🔍 5. Diagnostics & Outcome
Identifies missing podding objects (podid, podseq), low tmax timeout thresholds (<50ms), malformed user consent strings, and invalid devicetype values.
Ad server delivery conflicts and revenue loss frequently stem from misunderstandings of line item priority hierarchy (Sponsorship 4 vs Standard 8 vs Price Priority 12 vs Open Bidding) and dynamic price floor competition.
🎯 2. Context & Stakeholders
Ad Operations Teams, Yield Managers, Ad Server Solutions Engineers, and Publisher Monetization Leads.
Built an interactive ad server simulation workbench allowing engineers to test priority overrides, simulate external header bidding CPM inputs, and inspect step-by-step waterfall decision paths in real time.
🔍 5. Diagnostics & Outcome
Demonstrates why a $6.00 Price Priority line item loses to an eligible $0.00 Sponsorship line item due to guaranteed reservations, and isolates floor price blockages.
Google Ad ManagerWaterfall MechanicsDynamic AllocationPrice Floor Logic
Engineering Takeaway: Proves comprehensive operational knowledge of ad serving logic, priority rules, and yield management architecture.
CTV Dynamic Ad Insertion (DAI) & SSAI Manifest Playground
⚠️ 1. Problem (What was happening?)
Server-Side Ad Insertion frequently introduces playback buffering, audio loudness jumps, aspect ratio stretching, and broken quartile tracking beacons across Connected TV devices.
🎯 2. Context & Stakeholders
Connected TV (CTV) Publishers, SSAI Solution Architects, Video Engineering Teams, and OTT Streaming Platforms.
Constructed an interactive stream inspector that demonstrates synchronized video playback with ad segment timing graphs, SCTE-35 cue markers, and tracking beacon firing logs.
🔍 5. Diagnostics & Outcome
Verifies discontinuity tag placement, manifest timing accuracy, and client vs server beacon firing parity.
HLS / .m3u8SCTE-35VAST 4.2SSAI ArchitectureVideo Player API
Engineering Takeaway: Demonstrates end-to-end expertise in video ad protocols, SSAI stream stitching, and CTV playback troubleshooting.
AdTech Troubleshooting & Root-Cause Analysis (RCA) Knowledge Base
⚠️ 1. Problem (What was happening?)
AdTech onboarding and client technical escalations require structured, reproducible root-cause analysis across tracking discrepancies, API timeouts, and protocol errors.
🎯 2. Context & Stakeholders
Solution Engineers, Technical Account Managers (TAMs), and Level 2/3 AdTech Support Engineers.
Curated a comprehensive 100-question technical diagnostic repository with 10 deep incident case studies and 5 practical mock integration blueprints covering real-world AdTech problem solving.
🔍 5. Diagnostics & Outcome
Provides step-by-step playbooks for resolving VAST 303/405 error cascades, Prebid timeout tuning, and Sellers.json / SupplyChain verification.
Modern AdTech operations require bridging disparate ad server logs, SSP bidstreams, and buyer reporting APIs to detect impression discrepancies and pacing anomalies before billing reconciliation SLA breaches occur.
🎯 2. Context & Stakeholders
Technical Specialists, Solutions Architects, and Partner Integration Engineers.
3. Architecture Flow: AdTech REST API → Database Store → Python/Pandas Client → SQL Discrepancy Engine → Automated Underperformance Alert
🛠️ 4. Technical Approach & Implementation
Constructed a secure, read-only REST API endpoint layer paired with a standalone Python client and an advanced SQL query library (CTEs, Window Functions) that calculates real-time CTR, eCPM, and multi-partner billing variances.
🔍 5. Diagnostics & Outcome
Isolates render abort drop-offs, VAST 405 codec error surges by player device, and automated underperforming campaign alerts (CTR < 0.5%).
Engineering Takeaway: Proves hands-on engineering capabilities across REST APIs, Python data automation, SQL log analysis, and Model Context Protocol (MCP) AI integration.
IP / Proxy & User-Agent Filter Audit: Check if DSP IVT filters (IAS, DoubleVerify, MOAT) flagged cloud server or mobile proxy IP ranges.
2. CTV Video Ad Pod Delivery & SCTE-35 Failure Triage
Goal: Resolve playback buffering, blank ad pods, or early stream terminations in live SSAI.
SCTE-35 Cue Verification: Inspect manifest for #EXT-X-DATERANGE and verify PLANNED-DURATION matches actual commercial break duration.
Discontinuity Tag Audit: Confirm #EXT-X-DISCONTINUITY precedes and follows every stitched commercial chunk.
Codec & Bitrate Ladder Normalization: Verify transcoded video assets match the exact audio sample rate (48kHz) and video profile (H.264 Baseline/Main) of the main live stream.
Wrapper Hop Recursion: Verify VAST wrapper depth does not exceed 3 hops to prevent video player buffer stall timeouts (<2000ms).