RMN Technical Architect

Tata Consultancy Services
Greater London
2 months ago
Applications closed

1 week ago Be among the first 25 applicants

UK&I Technical Recruiter at Tata Consultancy Services

Role:RMN (Retail Media Network) Technical Architect

Job Type:Permanent

Location:London, UK (Hybrid)

Number of hours:Standard

Ready to utilize yourskills and experience in Retail Media Network Technology?

Join us as aRMN Technical Architect.

The Role

As aRMN Technical Architect,you will lead the design, development, and optimization of our Retail Media Network (RMN) technology stack. This role requires deep expertise in Ad-Tech, Mar-Tech, and cloud-based RMN solutions, with a strong focus on architecture, scalability, AI-driven automation, and seamless integration.

Key responsibilities:

  1. Define and implement the end-to-end architecture of RMN platforms, covering sponsored ads, programmatic DSP, self-service portals, and dynamic ad placements.
  2. Design scalable and modular RMN solutions, integrating Ad-Serving, Data Management Platforms (DMP), Customer Data Platforms (CDP), and Demand-Side Platforms (DSP).
  3. Ensure real-time bidding (RTB) and programmatic advertising capabilities within the RMN ecosystem.
  4. Develop a robust ad inventory management framework.
  5. Leverage AI/ML for audience segmentation, predictive analytics, and automated campaign optimization.
  6. Implement Generative AI for automated ad creation, content personalization, and A/B testing.
  7. Enhance Dynamic Creative Optimization (DCO) capabilities for personalized ad experiences.

Data & Integration Framework

  1. Define data ingestion, processing, and activation strategies across first-party, second-party, and third-party data sources.
  2. Ensure seamless API integrations with RMN partners, retail ecosystems, and marketing automation platforms.
  3. Develop closed-loop attribution models to measure ad performance effectively.

Ad-Tech Stack & Cloud Architecture

  1. Design RMN solutions leveraging Google Cloud, AWS, or Azure, ensuring high availability and low-latency performance.
  2. Optimize data pipelines, real-time analytics, and identity resolution mechanisms.
  3. Oversee privacy-compliant data handling (GDPR, CCPA) and secure identity frameworks.

Stakeholder Collaboration & Roadmap Execution

  1. Work closely with engineering, product, data science, and business teams to define the RMN technology roadmap.
  2. Engage with retailers, brands, and ad-tech vendors to expand monetization capabilities.
  3. Provide technical thought leadership on RMN innovations.

Your Profile

Essential skills/knowledge/experience:

  1. Strong experience in RMN architecture, Ad-Tech, and Mar-Tech solutions.
  2. Expertise in DSPs, SSPs, DMPs, CDPs, ad servers, and programmatic advertising.
  3. Proficiency in AI/ML applications for ad targeting, personalization, and optimization.
  4. Experience with Google Marketing Platform (GMP), Amazon Ads, The Trade Desk, or similar ecosystems.
  5. Strong understanding of cloud architectures (AWS, Azure, GCP) and big data technologies.
  6. Experience with privacy-first advertising (cookieless targeting, identity graphs).
  7. Strong API integration skills across marketing and retail platforms.
  8. Knowledge of real-time bidding (RTB), header bidding, and ad-exchange protocols.

TCS is consistently voted a Top Employer in the UK and globally. Our competitive salary packages feature pension, health care, life assurance, laptop, phone, access to extensive training resources and discounts within the larger Tata network.

Diversity, Inclusion and Wellbeing

Tata Consultancy Services UK&I is committed to meeting the accessibility needs of all individuals in accordance with the UK Equality Act 2010 and the UK Human Rights Act 1998.

We believe in building and sustaining a culture of equity and belonging where everyone can thrive. Our diversity and inclusion motto is ‘Inclusion without Exception’. Our continued commitment to Culture and Diversity is reflected across our workforce implemented through equitable workplace policies and processes.

If you are an applicant who needs any adjustments to the application process or interview, please contact usatwith the subject line: “Adjustment Request” or callTCS London Officeto request an adjustment. We welcome requests prior to you completing the application and at any stage of the recruitment process.

Next Steps

Due to a high volume of applications, we will be unable to contact each applicant individually on the status of their application. If you have not received a direct response within 30 days, then it should be deemed unsuccessful on this occasion.

Join us and do more of what matters. Apply online now.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.