Accolite Digital - Senior System Architect

Description:

Position Summary:

Client is seeking an experienced Senior Architect to guide the architectural design and set the strategic direction for developing its Retail Media On-Site Ad Server. This role is crucial in constructing a retailer-owned advertising stack that supports direct-sold, sponsored product, and programmatic demand, while maintaining a strong focus on privacy, performance, and merchandising requirements.

The Senior Architect will be responsible for creating scalable, low-latency systems that integrate AI/ML for relevance and optimization, utilize data analytics for accurate measurement, and support omnichannel capabilities to enhance onsite advertising and personalization for both retailers and CPG brands.

The successful candidate will report to the Director of Architecture or the VP of Engineering and will collaborate closely with engineering, product, data, and operations teams.

Key Responsibilities:

- Design and architect comprehensive end-to-end solutions for the On-Site Ad Server, encompassing essential services such as Edge Delivery API, Decision Service, Eligibility, Pacing & Caps, Inventory Management, SPA Blender, Creative/Template Service, and integration with supporting platforms like PIM (Product Information Manager), Audience Builder & CDP, and RCP (Retail Cloud Platform).

- Develop architectural blueprints, data models, and phased roadmaps, beginning with a minimum viable product (MVP) delivered in 34 months, followed by programmatic and machine learning enhancements.

- This includes the incorporation of AI/ML for click-through rate (CTR) and conversion rate (CR) modeling, predictive forecasting, campaign optimization, and personalized blending within onsite contexts such as search results pages (SRP), product listing pages (PLP), and recommendation carousels.

- Assess and recommend appropriate technologies for cloud infrastructure (e.g., AWS, Azure, GCP), real-time data processing (e.g., Kafka, Spark), low-latency key-value stores (e.g., Redis, Scylla), and security. Ensure scalable architecture, high throughput (peak QPS 3), reliability, and compliance with data privacy regulations (e.g., GDPR, CCPA) and retailer data handling agreements.

- Collaborate with cross-functional teams to integrate the ad server with Clients existing ecosystems, including incentives, loyalty programs, supply chain tools, personalization ad servers, coupons and rebates, DSP and off-site media, and ecommerce platforms. Guarantee seamless data flows for events, attributions, and catalogs.

- Conduct architectural reviews, threat modeling, and risk assessments, such as latency regressions, data leakage, and catalog conflicts. Propose mitigation strategies, including circuit breakers, feature flags, and fallback mechanisms, to enable agile development, safe deployments, and rapid iteration.

- Lead innovation in omnichannel strategies, with a focus on onsite elements like in-store digital integration, e-commerce personalization, shopper-linked media, and controls such as frequency capping, competitive separation, and merchandising rules.

- Promote sustainability and system efficiency by optimizing resource usage for waste reduction, supporting multi-tenant models with retailer-scoped partitioning, and maintaining performance budgets

- Mentor engineers and architects, providing technical guidance on best practices related to documentation, knowledge sharing, observability (including golden signals and distributed tracing), and operations (such as SLO dashboards and anomaly detection).

- Stay abreast of trends in retail media, ad technology, AI/ML (e.g., TensorFlow,PyTorchfor relevance models), and emerging technologies to inform architectural decisions and maintain Architecture Decision Records (ADRs).

Qualifications:

- Bachelors or Masters degree in Computer Science, Information Technology, or a closely related field; advanced degrees or certifications (such as TOGAF, AWS Certified Solutions Architect) are preferred.

- Over 10 years of experience in software architecture, with a specialization in building large-scale, data-intensive, real-time systems within retail, ad tech, or e-commerce environments.

- Proven track record in designing architectures for advertising platforms, media networks, or comparable domains, including hands-on experience with RMNs, programmatic advertising, on-site ad servers, or low-latency decision engines.

- Strong expertise in cloud platforms (e.g., AWS, Azure, GCP), containerization technologies (Kubernetes, Docker), real-time event streaming solutions (Kafka), big data tools (Spark, Hadoop), and OLAP/data warehouse platforms (Druid, ClickHouse, Snowflake).

- Practical experience with AI/ML frameworks (such as TensorFlow, PyTorch) and integrating machine learning models like CTR prediction and blending algorithms into production environments, employing exploration techniques such as epsilon-greedy and Thompson Sampling.

- Comprehensive understanding of API design (REST, GraphQL, gRPC), microservices, event-driven architectures, security best practices (including consent gating, encryption, least-privilege access), and multi-tenant systems.

- Familiarity with the retail sector, including omnichannel retail, consumer data analytics, supply chain integrations, and ecommerce platforms.

- Strong problem-solving, communication, and collaboration skills, with an ability to convey complex technical concepts to non-technical stakeholders.

Preferred Skills:

- Experience with retail media-specific tools, such as DSP/SSP integrations, real-time bidding systems (like Prebid Server), shopper behavior analytics, or on-site ad products such as SPA (Sponsored Product Ads) and SDA (Sponsored Display Ads).

- Background in sustainability-oriented architecture, healthcare data systems, or privacy-centric designs (including data protection impact assessments and automated policy tests), reflecting the diverse portfolio of Client.

- Proficiency in DevOps practices, including CI/CD pipelines, automation tools (Terraform, Ansible), and performance optimization techniques (such as caching strategies and ensuring idempotency).