principal data architect

TripleLift

<div><div>About TripleLift

We're TripleLift, an advertising platform on a mission to elevate digital advertising through beautiful creative, quality publishers, actionable data and smart targeting. Through over 1 trillion monthly ad transactions, we help publishers and platforms monetize their businesses. Our technology is where the world's leading brands find audiences across online video, connected television, display and native ads. Brand and enterprise customers choose us because of our innovative solutions, premium formats, and supportive experts dedicated to maximizing their performance.
As part of the Vista Equity Partners portfolio, we are NMSDC certified, qualify for diverse spending goals and are committed to economic inclusion. Find out how TripleLift raises up the programmatic ecosystem at triplelift.com.</div><h2 class="jobSectionHeader">
Overview</h2> 


The Senior/Principal Identity and API Architect plays a critical role in driving TripleLift's identity infrastructure and API security strategy within the Exchange team, directly influencing how we authenticate and authorize publishers, buyers, and platform partners across our programmatic marketplace. In this position, you will partner closely with Engineering, Product, and Services teams to design and own the end-to-end identity architecture that underpins our Exchange's security, scalability, and interoperability. This is an exciting opportunity for someone who wants to build a best-in-class identity platform from the ground up, shaping how TripleLift authenticates billions of programmatic transactions while serving as a strategic thought partner to Exchange leadership on API governance and access control. 

<h2 class="jobSectionHeader">
Responsibilities</h2> 

<ul>
<li>Architect and own TripleLift's end-to-end identity platform, including tenant models, SSO integrations, machine-to-machine authentication, and delegated administration for publishers and demand partners.</li>
<li>Design and implement Auth0 tenant architecture, including custom domains, enterprise connections, Actions/Rules, and token lifecycle management (refresh rotation, session policies, JWKS).</li>
<li>Define and enforce OAuth 2.0 and OIDC flows across the Exchange &mdash; including PKCE, M2M client credentials, and device authorization &mdash; ensuring secure and consistent authentication for all platform participants.</li>
<li>Build and operate multi-tenant authorization models using OpenFGA or comparable ReBAC systems (e.g., SpiceDB, Ory Keto), enabling fine-grained access control across publisher hierarchies (networks, properties, seats, users).</li>
<li>Own the API gateway layer, designing rate limiting, scoped token validation, mTLS enforcement, and consistent error semantics across Traefik, Kong, AWS API Gateway, or equivalent infrastructure.</li>
<li>Lead publisher-side identity integrations, including federated SSO (SAML 2.0, OIDC) for enterprise onboarding, delegated self-service administration, and integration of first-party data and authenticated traffic signals into programmatic decisioning.</li>
<li>Lead demand-side identity integrations, including DSP and agency API authentication (OAuth 2.0 M2M, API key management), partner onboarding flows, and identity traceability across bid request/response flows for audit, fraud detection, and deal enforcement.</li>
<li>Manage AWS identity and API infrastructure, including IAM roles and cross-account trust, Cognito integration patterns, Secrets Manager and KMS for credential lifecycle, and STS-based service-to-service auth in multi-account environments.</li>
<li>Establish and maintain identity and API security standards, conducting threat modeling, reviewing integrations for compliance with RBAC/ABAC/ReBAC policies, and responding to security incidents.</li>
<li>Serve as the internal subject-matter expert on identity and API architecture, partnering with Engineering, Legal, and Partnerships to advise on protocol selection, vendor evaluation, and regulatory considerations (e.g., GDPR, CCPA as they relate to identity signals).</li>
<li>Mentor engineers across the Exchange team on identity best practices, OAuth/OIDC protocol nuances, and secure API design patterns.</li></ul> 

<h2 class="jobSectionHeader">
Education &amp; Requirements</h2> 

<ul>
<li>8+ years of software engineering or platform architecture experience, with at least 4 years focused on identity, IAM, or API security</li>
<li>2+ years of hands-on production experience with Okta's Auth0, including:</li>
<li><ul><li>Tenant architecture, custom domains, and enterprise connections</li>
<li>Actions/Rules/Hooks and the Auth0 Management API</li>
<li>OIDC/OAuth 2.0 flows including PKCE, M2M client credentials, and device authorization</li>
<li>Token customization, refresh token rotation, and session management</li>
<li>Production experience with OpenFGA or a comparable relationship-based access control (ReBAC) system (e.g., Zanzibar-derived implementations, Ory Keto, SpiceDB)</li>
</ul></li><li>Deep fluency in OAuth 2.0, OpenID Connect, SAML 2.0, JWT, and JWKS</li>
<li>Demonstrated AWS identity and API infrastructure experience, including:</li>
<li><ul><li>IAM roles, policies, and cross-account trust relationships</li>
<li>API Gateway (REST and HTTP APIs), Lambda authorizers, and Cognito integration patterns</li>
<li>Secrets Manager and KMS for credential and key lifecycle management</li>
<li>STS and service-to-service authentication in distributed, multi-account environments</li>
</ul></li><li>Experience designing and operating API gateway layers at scale, including hands-on work with one or more of: Traefik, Kong, AWS API Gateway, or equivalent &mdash; encompassing rate limiting, scoped token validation, mTLS, and consistent error semantics</li>
<li>Experience with publisher-side identity integrations:</li>
<li><ul><li>Federated SSO (SAML 2.0, OIDC) for publisher onboarding and enterprise identity provider connections</li>
<li>Multi-tenant identity models supporting publisher hierarchies: networks, properties, seats, and users</li>
<li>Delegated administration patterns enabling publishers to self-manage sub-accounts and user roles</li>
<li>Integration with publisher identity signals for decisioning (authenticated traffic, first-party data tokens)</li>
</ul></li><li>Experience with demand-side identity integrations:</li>
<li><ul><li>DSP and agency API authentication: OAuth 2.0 M2M, API key management, and scoped access models</li>
<li>Partner onboarding flows supporting both self-serve and managed programmatic demand</li>
<li>Identity traceability across bid request/response flows for audit, fraud detection, and deal enforcement</li>
<li>Integration with buyer identity infrastructure including agency trading desk and DSP seat management</li>
</ul></li><li>Demonstrated ability to model complex, multi-tenant authorization hierarchies using RBAC, ABAC, or ReBAC</li>
<li>Proficiency in at least one backend language (Go, Java, or Python preferred)</li>
</ul><div>
Life at TripleLift

At TripleLift, we're a team of great people who like who they work with and want to make everyone around them better. This means being positive, collaborative, and compassionate. We hustle harder than the competition and are continuously innovating.
Learn more about TripleLift and our culture by visiting our LinkedIn Life page.

Establishing People, Culture and Community Initiatives

At TripleLift, we are committed to building a culture where people feel connected, supported, and empowered to do their best work. We invest in our people and foster a workplace that encourages curiosity, celebrates shared values, and promotes meaningful connections across teams and communities. We want to ensure the best talent of every background, viewpoint, and experience has an opportunity to be hired, belong, and develop at TripleLift. Through our People, Culture, and Community initiatives, we aim to create an environment where everyone can thrive and feel a true sense of belonging.

Privacy Policy

Please see our Privacy Policies on our TripleLift and 1plusX websites.

TripleLift does not accept unsolicited resumes from any type of recruitment search firm. Any resume submitted in the absence of a signed agreement will become the property of TripleLift and no fee shall be due.</div></div>

Principal Identity and API Architect

Faculty

<div><h2 class="jobSectionHeader">Why Faculty? 
</h2> 
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we&rsquo;ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don&rsquo;t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we&rsquo;re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you&rsquo;ll be empowered to envision its most powerful applications, and to make them happen.<h2 class="jobSectionHeader">
About the team</h2>
Our Retail and Consumer experts are dedicated to helping clients in an industry which is being transformed by new technologies and evolving consumer expectations. Leveraging over a decade of experience in Applied AI, we combine exceptional technical and delivery expertise to empower businesses to adapt and thrive.
#LI-PRIO<h2 class="jobSectionHeader">
About the role</h2>
As a Principal Data Scientist, you'll serve as a recognised authority and strategic force across the organisation, shaping not just how we deliver but how we evolve. You will define our technical vision at the highest level, influence organisation-wide strategy, and take ultimate ownership of our most critical, complex, and commercially significant programmes. This position goes beyond project delivery &mdash; you are a multiplier of capability, a trusted partner to senior leadership, and a key driver of long-term competitive differentiation.<h2 class="jobSectionHeader">
What you'll be doing:</h2><ul><li>
Defining and owning the long-term technical vision for the practice, setting standards that raise the bar across the entire organisation.</li><li>
Architecting and overseeing the delivery of flagship, business-critical programmes &mdash; spanning multiple workstreams, teams, and client organisations.</li><li>
Driving organisation-wide adoption of innovation, tooling, and best practices &mdash; influencing how the entire Data Science craft evolves.</li><li>
Cultivating senior talent across the organisation &mdash; coaching leads and managers, building capability pipelines, and embedding a culture of technical excellence.</li><li>
Acting as the senior technical voice in C-suite and executive client engagements, shaping strategic direction and securing long-term partnerships.</li><li>
Leading on the most strategically significant sales opportunities, providing technical authority that differentiates our proposition and wins high-value engagements.</li><li>
Partnering with Engineering, Commercial, and Infrastructure leadership to align technical strategy with broader business goals and growth ambitions.</li></ul><h2 class="jobSectionHeader">
Who we're looking for:</h2><ul><li>
You are a recognised expert in multiple machine learning domains, with the technical breadth to make sound judgements across the full data science landscape.</li><li>
You have a proven track record of shaping technical strategy at an organisational level &mdash; not just within projects, but across business units and leadership forums.</li><li>
You have led the delivery of large-scale, high-ambiguity programmes and can bring clarity, structure, and momentum to the most complex situations.</li><li>
You are a skilled developer of senior people &mdash; coaching leads and managers, building capability, and shaping a high-performance culture.</li><li>
You operate naturally at the executive level &mdash; with clients and internal stakeholders alike &mdash; as a trusted advisor who can translate technical thinking into commercial outcomes.</li><li>
You have a visible external profile &mdash; through publications, conference contributions, open-source leadership, or industry influence &mdash; that reflects your standing in the field.</li><li>
You think beyond the immediate &mdash; identifying emerging opportunities and risks and proactively shaping the organisation's response before they arrive.</li></ul><h2 class="jobSectionHeader">
Our Interview Process</h2><ul><li>
Talent Team Screen (30 minutes)</li><li>
Introduction to the team (30 minutes)</li><li>
Take Home Technical Assessment</li><li>
Technical Interview (90 minutes)</li><li>
Commercial Interview (60 minutes)</li></ul><h2 class="jobSectionHeader">
Our Recruitment Ethos</h2>
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We&rsquo;re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits:<ul><li>
Unlimited Annual Leave Policy</li><li>
Private healthcare and dental</li><li>
Enhanced parental leave</li><li>
Family-Friendly Flexibility &amp; Flexible working</li><li>
Sanctus Coaching</li><li>
Hybrid Working</li></ul>
If you don&rsquo;t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.</div>

Principal Data Scientist

<div><h2 class="jobSectionHeader">Why Faculty? 
</h2> 
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we&rsquo;ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don&rsquo;t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we&rsquo;re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you&rsquo;ll be empowered to envision its most powerful applications, and to make them happen.<h2 class="jobSectionHeader">
About the role</h2>
As a Principal Machine Learning Engineer, you'll serve as the definitive technical authority on ML engineering across the organisation, setting the standard for how we design, build, and scale AI systems. You will own the architectural vision for our most complex and high-stakes programmes, influence engineering strategy at an organisational level, and act as a trusted partner to senior leadership and executive clients.
This role goes beyond leading projects, you are a force multiplier who shapes the engineering culture, elevates the capability of those around you, and ensures our technical foundations are built to last.<h2 class="jobSectionHeader">
What you'll be doing:</h2><ul><li>
Defining and owning the organisation-wide technical vision for ML engineering, establishing architectural standards and engineering practices that scale across teams and clients.</li><li>
Overseeing the end-to-end delivery of flagship, business-critical ML programmes, spanning multiple workstreams, engineering teams, and client organisations.</li><li>
Driving the strategic adoption of new technologies, platforms, and ways of working, influencing how the entire engineering craft evolves.</li><li>
Cultivating senior engineering talent, coaching leads and managers, building capability pipelines, and embedding a culture of technical rigour and excellence.</li><li>
Acting as the principal technical voice in C-suite and executive client engagements, shaping AI strategy and securing long-term strategic partnerships.</li><li>
Leading on the most significant sales and pre-sales opportunities, providing architectural authority that differentiates our proposition and wins high-value engagements.</li><li>
Partnering with Data Science, Commercial, and Infrastructure leadership to align ML engineering strategy with broader business goals and growth ambitions.</li></ul><h2 class="jobSectionHeader">
Who we're looking for:</h2><ul><li>
You are a recognised ML engineering authority, able to go exceptionally deep across multiple domains and provide definitive technical judgement on the hardest problems.</li><li>
You have mastery of Python and a proven track record of designing and operationalising production-grade ML systems at scale, across multiple frameworks and paradigms.</li><li>
You are an expert across multiple major Cloud Solution Providers and have set the architectural direction for complex, full-stack AI platforms spanning multiple organisations.</li><li>
You have deep expertise in containerisation, orchestration, and MLOps at scale, and have established the standards others follow.</li><li>
You have a proven track record of developing senior engineering talent, coaching leads and managers, building capability, and shaping high-performance engineering cultures.</li><li>
You have a visible external profile, through publications, conference contributions, open-source leadership, or industry influence, that reflects your standing in the field.</li><li>
You operate naturally at the executive level, translating complex ML engineering decisions into commercial outcomes and proactively shaping the strategic direction of client engagements.</li></ul><h2 class="jobSectionHeader">
Our Interview Process</h2><ul><li>
Talent Team Screen (30 minutes)</li><li>
Introduction to the role (45 minutes)</li><li>
Pair Programming Interview (90 minutes)</li><li>
System Design Interview (90 minutes)</li><li>
Commercial &amp; Leadership Interview (60 minutes)</li></ul><h2 class="jobSectionHeader">
Our Recruitment Ethos</h2>
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We&rsquo;re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits:<ul><li>
Unlimited Annual Leave Policy</li><li>
Private healthcare and dental</li><li>
Enhanced parental leave</li><li>
Family-Friendly Flexibility &amp; Flexible working</li><li>
Sanctus Coaching</li><li>
Hybrid Working</li></ul>
If you don&rsquo;t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.</div>

Principal Machine Learning Engineer

<div><div><div>Job ID: R0055886</div>
</div><div><div><div><div><div>Location</div>
<div>London, Middlesex</div>
</div></div></div><div></div><div><div><div><div>Hours/week</div>
<div>37.5 hrs/week</div>
</div></div></div><div></div><div><div><div><div>Payrate range</div>
<div>Unknown</div>
</div></div></div></div><div><div>We don&rsquo;t just believe in better. We make it happen.
Better content. Better products. And better careers. 
Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, Sky Stream to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. 
Role/Team overview
Data science is at the heart of decision making in Sky and drives a majority of decisions across marketing, customer interactions and customer services at Sky. In the Advanced Analytics team, we are scaling up our data science practice to transform how we manage customers across all life cycles for both experience profitability. We have built and successfully deployed intelligence into Sky and are already delivering realisable value into the business. We gather a very large amount of data on customer behaviours and interactions and are looking for data scientists to extract value from our data assets and maximise customer value. 
What you&rsquo;ll do:
<ul><li>Producing high quality, actionable insights through advanced analytics and cutting-edge predictive algorithms: work as a self-starter and be actively curious about what numbers are telling us and how they can be actioned upon to improve our customer experience
</li></ul><ul><li>Designing and implementing innovative and commercially led data science and insights roadmaps with stakeholders (marketing, retention, service, finance) to improve the way they make decisions: hypotheses-led problem solving to deliver solutions to business problems.
</li></ul><ul><li>Engage with our technology teams and data engineers to build compliant, efficient and scalable solutions
</li></ul><ul><li>Strengthen our internal data science capabilities by continuously innovating and driving new ideas, building technology partnerships with our vendors, training and developing our people and creating a world class data science team at Sky
</li></ul><ul><li>Engage with key stakeholders (marketing, retention, service, finance) to understand business objectives and support these objectives through best use of advanced analytics approaches.
</li></ul><ul><li>Responsible for identifying the best analytical techniques, developing the solution, creating a framework for testing the solution and measuring the incremental value to the business from the solution 
</li></ul>What you&rsquo;ll bring:
<ul><li>Strong track record delivering end‑to‑end data science solutions (preferably B2C) in cloud environment
</li></ul><ul><li>Deep expertise in machine learning and statistical modelling, with proven impact in areas like personalisation, churn, pricing, and optimisation
</li></ul><ul><li>Ability to quickly understand a business objective, problem solving to create an analytical solution and develop a solution alongside stakeholders are essential
</li></ul><ul><li>Commercial knowledge and applications of data science to drive commercial value is a must &ndash; everything we do drives value into the business
</li></ul><ul><li>Hands‑on experience with Generative AI and LLMs, including prompt engineering, fine‑tuning, evaluation, and production deployment
</li></ul><ul><li>Strong command of modern data stacks, including Python, SQL, Spark, BigQuery, and Snowflake
</li></ul><ul><li>Clear communication skills, able to explain complex AI concepts, including LLMs and agentic systems, to both technical and non‑technical audiences 
</li></ul>Benefits and perks 
There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here&rsquo;s a taster:
<ul><li>Sky Q, for the TV you love all in one place
</li></ul><ul><li>The magic of Sky Glass at an exclusive rate
</li></ul><ul><li>A generous pension package
</li></ul><ul><li>Private healthcare
</li></ul><ul><li>Discounted mobile and broadband
</li></ul><ul><li>A wide range of Sky VIP rewards and experiences 
</li></ul>How you&rsquo;ll work
We've adopted a hybrid working approach to give more flexibility on where and how we work. The hybrid working expectations for this role are 2 days in the office per week. 
Your office space: 
Osterley:
Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There&rsquo;s also plenty of bike shelters and showers.
On campus, you&rsquo;ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed and even get pampered at our beauty salon. 
We'd love to hear from you
Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It&rsquo;s a place where you can explore what if, how far, and what next. 
But better doesn&rsquo;t stop at what we do, it&rsquo;s how we do it, too. We embrace each other&rsquo;s differences. We support our community and contribute to a sustainable future for our business and the planet.
If you believe in better, we&rsquo;ll back you all the way. 
Just so you know: if your application is successful, we&rsquo;ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer. 
Who we are
We&rsquo;re Sky, a leading media and entertainment company who connect millions with entertainment, sports, news and arts through innovative products and services. Working with us means you&rsquo;ll be bringing the joy of a better experience to more people, every day. All so we can do better and deliver better for our customers, colleagues and society. 
We&rsquo;re an equal opportunity employer and value diversity at our company. We're a Disability Confident Accredited Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need as early as you can. 
Just so you know: if your application is successful, we&rsquo;ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer. 
To be eligible for this role you are required to have the appropriate right to work in the UK. Please be aware Sky does not offer sponsorship for this position. 
To find out more about working with us, search #LifeAtSky on social media.</div></div></div>

Mastercard

<div>Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we&rsquo;re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Senior Principal Agentic Platforms Architect
Overview
 
 
The AI Center of Excellence is seeking a Senior Principal Agentic Platforms Architect to lead the technical vision, architecture, and hands-on development of Mastercard's enterprise agentic AI platforms. This role demands deep, demonstrated expertise in building and shipping production-grade AI and agentic systems at enterprise scale, combined with the architectural rigor required to operate within one of the most highly regulated and security-conscious environments in the world. Reporting to senior leadership, you will own the E2E platform architecture for agentic AI systems, from runtime orchestration and governance infrastructure through to production deployment and operational lifecycle management. This is not a strategy-only role. You will write code, review code, and hold the team to the highest standards of engineering excellence. The right candidate has spent their career building AI systems that run in production, not prototypes, not proofs of concept, but systems that operate at scale, under load, and under scrutiny 
 
Role
 
 
<ul><li>Serve as the principal technical authority for agentic AI platform architecture, owning the design and evolution of runtime environments, governance layers, orchestration engines, and multi-tenancy infrastructure that support enterprise-grade AI agent deployment</li></ul> 
<ul><li>Lead hands-on architecture and development of agentic systems, including agent orchestration frameworks, tool and model integration layers, policy enforcement engines, guardrail systems, behavioral monitoring pipelines, and evaluation infrastructure</li></ul> 
<ul><li>Design and implement scalable, resilient platform architectures that support multi-agent coordination, A2A communication protocols, memory governance, and real-time observability across distributed deployments</li></ul> 
<ul><li>Drive the technical strategy for model integration and abstraction, enabling model-agnostic agent execution across multiple providers while enforcing cost optimization, routing intelligence, and governance controls at the platform level</li></ul> 
<ul><li>Architect and build API-first platform interfaces that enable both internal teams and external consumers to build, deploy, govern, and operate AI agents through programmatic, language-agnostic access patterns</li></ul> 
<ul><li>Define and enforce engineering standards, code quality practices, and architectural governance across the platform engineering team, ensuring every component meets production-grade requirements for security, resilience, performance, and compliance</li></ul> 
<ul><li>Provide deep technical leadership on agentic AI design patterns, including retrieval-augmented generation, tool calling via Model Context Protocol, multi-step orchestration, human-in-loop workflows, and autonomous decision-making architectures</li></ul> 
<ul><li>Act as a trusted technical advisor to senior leadership, translating complex platform architecture decisions into clear, business-oriented language that supports informed decision-making at the executive level</li></ul> 
<ul><li>Mentor and develop a high-performing engineering team, fostering a culture of technical excellence, intellectual honesty, rigorous code review, and continuous improvement</li></ul> 
<ul><li>Produce and maintain authoritative architectural documentation, including system design documents, architecture decision records, and integration specifications that meet Mastercard's engineering principles and security standards</li></ul> 
All About You
 
 
<ul><li>15+ years of hands-on experience in software engineering and AI engineering, with a significant and demonstrable portion spent designing, building, and shipping AI and machine learning systems to production at enterprise scale</li></ul> 
<ul><li>Proven track record of architecting and delivering agentic AI systems, autonomous agents, multi-agent orchestration platforms, or AI-powered automation systems that operate in production with real users, real data, and real consequences</li></ul> 
<ul><li>Deep hands-on coding proficiency. You write production code, you review production code, and you hold others to the same standard. This is a building role, not a diagram-drawing role</li></ul> 
<ul><li>Advanced expertise in Python and modern AI/ML frameworks, with hands-on experience across agentic toolkits such as LangChain, LangGraph, CrewAI, or equivalent orchestration frameworks</li></ul> 
<ul><li>Strong architectural experience with cloud-native platforms including AWS, Databricks, and Kubernetes, with demonstrated ability to design for high availability, fault tolerance, and horizontal scalability</li></ul> 
<ul><li>Deep understanding of AI governance, trust, and safety architectures, including guardrail systems, policy engines, behavioral analytics, evaluation frameworks, red teaming methodologies, and compliance mapping</li></ul> 
<ul><li>Experience designing and building multi-tenant platforms with fine-grained access control, workspace isolation, and enterprise-grade identity and authorization systems</li></ul> 
<ul><li>Proven ability to design API-first architectures, RESTful interfaces, and SDK abstractions that serve both internal platform teams and external consumers</li></ul> 
<ul><li>Strong understanding of data architectures including Delta Lake, data lakehouse patterns, vector databases and retrieval-augmented generation pipelines</li></ul> 
<ul><li>Demonstrated experience with tool calling architectures and model-agnostic integration patterns across multiple LLM providers</li></ul> 
<ul><li>Exceptional communicator who can articulate deeply technical architecture decisions to engineering teams and translate complex platform concepts into business language for non-technical stakeholders</li></ul> 
<ul><li>Known for building trust, holding high standards, and mentoring engineers. You make the people around you better. Motivated by hard problems, not titles. You bring intellectual curiosity, resilience, and relentless energy to complex technical challenges</li></ul> 
<ul><li>Bachelor's degree in Computer Science, Engineering, or a related field. Advanced degree preferred but not required if the experience speaks for itself</li></ul>
Corporate Security Responsibility 
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:<ul><li>
Abide by Mastercard&rsquo;s security policies and practices;</li><li>
Ensure the confidentiality and integrity of the information being accessed;</li><li>
Report any suspected information security violation or breach, and</li><li>
Complete all periodic mandatory security trainings in accordance with Mastercard&rsquo;s guidelines.</li></ul></div>

Senior Principal Agentic Platforms Architect

Accenture

<div>YOU ARE
As a hands-on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands-on &mdash; you will spend the majority of your time in the architecture and engineering of real-world AI solutions across classical machine learning, generative AI, and agentic systems, delivering these within active client engagements. You will translate requirements into concrete architecture decisions: selecting design patterns, evaluating and benchmarking technical frameworks, assembling reusable components, and making deliberate technology choices that balance innovation with enterprise-grade reliability. You will design and build AI agent architectures &mdash; including multi-agent orchestration, tool use, skills use, and memory systems &mdash; and work hands-on with foundation models through fine-tuning, retrieval-augmented generation (RAG), and custom model integration. A part of your work will also involve engineering the AI context layer that makes these systems intelligent in practice &mdash; connecting enterprise knowledge bases, structured and unstructured data sources, and domain-specific content so that AI outputs are grounded, accurate, and relevant to the client's business. You will design and validate systems against enterprise non-functional requirements across security, observability, governance, performance, and scalability. A core output of this is the production of tangible engineering and architecture deliverables. This means writing and owning software components &mdash; building, integrating, and testing AI system modules as a practitioner &mdash; alongside producing detailed architecture artifacts including architecture decision records (ADRs), component diagrams, data flow diagrams, and integration specifications that guide and enable broader engineering teams. You will work with cross-functional delivery teams alongside data engineers, ML engineers, and application developers, and this is an opportunity to develop deep expertise across the full AI architecture stack, sharpen your engineering instincts on complex, real-world problems, and build a foundation for growing into a lead or principal architect over time.
THE WORK<ul><li>
Independently design, build, and deliver software components across the AI architecture &mdash; owning them end to end from design through implementation, integration, and testing as a hands-on practitioner</li><li>
Design and build AI agent architectures &mdash; including individual agents, their prompts, tools, and skills, multi-agent orchestration, and memory systems &mdash; making deliberate design pattern and technology choices</li><li>
Design and implement agent orchestration patterns that handle task handoffs, communication, state management, and error recovery, validating them through hands-on prototyping</li><li>
Evaluate multiple design options and technical approaches, making deliberate, justified design choices that balance capability, cost efficiency, performance, and enterprise-grade reliability</li><li>
Design, build, and run evaluation strategies and harnesses that measure agent and system quality on metrics such as accuracy, relevance, and faithfulness, translating findings into design improvements</li><li>
Architect and implement foundation model integrations &mdash; selecting the right models, invocation patterns, and customization approaches (fine-tuning, RAG, custom integration) based on capability, cost, and performance trade-offs</li><li>
Design and build model adaptation and fine-tuning pipelines, applying working knowledge of transformer-based architectures to inform model selection and optimization</li><li>
Design and build the AI context layer &mdash; including context graph design and ingestion pipelines that parse, chunk, enrich, and index structured and unstructured enterprise content, and the retrieval components that ground AI outputs in the client's knowledge</li><li>
Build embedding, vector storage, and retrieval (semantic, hybrid, reranking) into end-to-end RAG pipelines, applying integration patterns that connect to enterprise data sources</li><li>
Design and implement context assembly and memory components that manage prompts, context windows, and conversational state for grounded, accurate outputs</li><li>
Identify, design, and build reusable components and solution patterns that accelerate delivery and can be templated across engagements</li><li>
Design for cost efficiency and performance &mdash; optimizing model usage, inference patterns, caching, and resource utilization to meet target latency, throughput, and cost objectives</li><li>
Design, build, and validate systems against enterprise non-functional requirements &mdash; implementing guardrails, prompt-injection defenses, PII handling, and access controls for security and Responsible AI</li><li>
Build governance controls including versioning, audit logging, and lineage tracking, and produce the model documentation that keeps systems auditable</li><li>
Build observability into systems &mdash; logging, tracing, monitoring, alerting, and cost tracking &mdash; to ensure AI solutions remain healthy, performant, and scalable in production</li><li>
Produce detailed architecture artifacts &mdash; including architecture decision records (ADRs), architecture blueprints, design documents, agent orchestration and integration pattern specifications, component and data flow diagrams &mdash; that guide and enable broader engineering teams</li><li>
Continuously learn, evaluate, and apply new design patterns, frameworks, and technologies across the fast-evolving AI landscape, balancing innovation with enterprise-grade reliability</li><li>
Collaborate with cross-functional delivery teams &mdash; data engineers, ML engineers, and application developers &mdash; to translate requirements into concrete architecture decisions that meet stakeholder needs</li></ul></div>
 
<div>EDUCATION<ul><li><ul><li>Bachelor's Degree or equivalent</li></ul></li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience in designing &amp; deploying AI / ML solutions using at least one cloud vendor as an AI/ML architect.</li><li>
Recent experience in the Agentic, LLM and Generative AI space.</li><li>
Experience architecting and operationalizing LLM driven application architecture patterns.</li><li>
Experience coding and engineering, machine learning, deep learning and NLP solutions and applications. Coding experience using python</li></ul></div>

AI LLM Technology Architecture Specialist

<div>YOU ARE
As a hands-on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands-on &mdash; you will spend the majority of your time in the architecture and engineering of real-world AI solutions across classical machine learning, generative AI, and agentic systems, delivering these within active client engagements.
You will translate requirements into concrete architecture decisions: selecting design patterns, evaluating and benchmarking technical frameworks, assembling reusable components, and making deliberate technology choices that balance innovation with enterprise-grade reliability. You will design and build AI agent architectures &mdash; including multi-agent orchestration, tool use, skills use, and memory systems &mdash; and work hands-on with foundation models through fine-tuning, retrieval-augmented generation (RAG), and custom model integration.
A part of your work will also involve engineering the AI context layer that makes these systems intelligent in practice &mdash; connecting enterprise knowledge bases, structured and unstructured data sources, and domain-specific content so that AI outputs are grounded, accurate, and relevant to the client's business.
You will design and validate systems against enterprise non-functional requirements across security, observability, governance, performance, and scalability.
A core output of this is the production of tangible engineering and architecture deliverables. This means writing and owning software components &mdash; building, integrating, and testing AI system modules as a practitioner &mdash; alongside producing detailed architecture artifacts including architecture decision records (ADRs), component diagrams, data flow diagrams, and integration specifications that guide and enable broader engineering teams.
You will work with cross-functional delivery teams alongside data engineers, ML engineers, and application developers, and this is an opportunity to develop deep expertise across the full AI architecture stack, sharpen your engineering instincts on complex, real-world problems, and build a foundation for growing into a lead or principal architect over time.
THE WORK<ul><li>
Independently design, build, and deliver software components across the AI architecture &mdash; owning them end to end from design through implementation, integration, and testing as a hands-on practitioner</li><li>
Design and build AI agent architectures &mdash; including individual agents, their prompts, tools, and skills, multi-agent orchestration, and memory systems &mdash; making deliberate design pattern and technology choices</li><li>
Design and implement agent orchestration patterns that handle task handoffs, communication, state management, and error recovery, validating them through hands-on prototyping</li><li>
Evaluate multiple design options and technical approaches, making deliberate, justified design choices that balance capability, cost efficiency, performance, and enterprise-grade reliability</li><li>
Design, build, and run evaluation strategies and harnesses that measure agent and system quality on metrics such as accuracy, relevance, and faithfulness, translating findings into design improvements</li><li>
Architect and implement foundation model integrations &mdash; selecting the right models, invocation patterns, and customization approaches (fine-tuning, RAG, custom integration) based on capability, cost, and performance trade-offs</li><li>
Design and build model adaptation and fine-tuning pipelines, applying working knowledge of transformer-based architectures to inform model selection and optimization</li><li>
Design and build the AI context layer &mdash; including context graph design and ingestion pipelines that parse, chunk, enrich, and index structured and unstructured enterprise content, and the retrieval components that ground AI outputs in the client's knowledge</li><li>
Build embedding, vector storage, and retrieval (semantic, hybrid, reranking) into end-to-end RAG pipelines, applying integration patterns that connect to enterprise data sources</li><li>
Design and implement context assembly and memory components that manage prompts, context windows, and conversational state for grounded, accurate outputs</li><li>
Identify, design, and build reusable components and solution patterns that accelerate delivery and can be templated across engagements</li><li>
Design for cost efficiency and performance &mdash; optimizing model usage, inference patterns, caching, and resource utilization to meet target latency, throughput, and cost objectives</li><li>
Design, build, and validate systems against enterprise non-functional requirements &mdash; implementing guardrails, prompt-injection defenses, PII handling, and access controls for security and Responsible AI</li><li>
Build governance controls including versioning, audit logging, and lineage tracking, and produce the model documentation that keeps systems auditable</li><li>
Build observability into systems &mdash; logging, tracing, monitoring, alerting, and cost tracking &mdash; to ensure AI solutions remain healthy, performant, and scalable in production</li><li>
Produce detailed architecture artifacts &mdash; including architecture decision records (ADRs), architecture blueprints, design documents, agent orchestration and integration pattern specifications, component and data flow diagrams &mdash; that guide and enable broader engineering teams</li><li>
Continuously learn, evaluate, and apply new design patterns, frameworks, and technologies across the fast-evolving AI landscape, balancing innovation with enterprise-grade reliability</li><li>
Collaborate with cross-functional delivery teams &mdash; data engineers, ML engineers, and application developers &mdash; to translate requirements into concrete architecture decisions that meet stakeholder needs</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience in designing &amp; deploying AI / ML solutions using at least one cloud vendor as an AI/ML architect.</li><li>
Experience in the Agentic, LLM and Generative AI space.</li><li>
Experience architecting and operationalizing LLM driven application architecture patterns.</li><li>
Expertise in coding with Python and engineering, machine learning, deep learning and NLP solutions and applications.</li></ul></div>

AI LLM Technology Architecture Assoc Manager

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