Solution Architect (AWS, AI, Python)

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

Job Description

• Role Overview

  We are seeking a highly experienced Senior Solution Architect to lead the design and delivery of enterprise-grade, secure, and scalable cloud-native solutions. This role sits at the intersection of AI strategy, data engineering, and platform architecture within a highly regulated environment. You will be instrumental in shaping the technical direction of next-generation AI and data platforms, from early-stage proof of concepts through to production-grade architectures.

• Key Responsibilities

• Cloud Architecture & Solution Design

• Design, validate, and prove complex end-to-end cloud architectures on AWS, spanning batch processing, real-time streaming, and event-driven patterns.
• Architect solutions leveraging AWS services including EC2, S3, Lambda, SNS, SQS, Kinesis, AWS Glue, Athena, Redshift, and EMR/EMR Serverless.
• Lead the design of Data Warehouse and Data Lake solutions, ensuring scalability, performance, and cost efficiency.
• Define and govern architectural frameworks, patterns, and reusable design blueprints for use across engineering teams.

• AI Strategy & Generative AI

• Define and drive the organisation's AI strategy, aligning AI initiatives with broader business and technology goals.
• Architect and deliver Generative AI (GenAI) solutions, including LLM integration, prompt engineering patterns, and AI-powered application design.
• Design, build, and deploy MCP (Model Context Protocol) servers and AI Agents, covering the full lifecycle from development to production deployment on AWS.

• Data Engineering & Pipeline Design

• Design and deliver robust end-to-end data pipeline architectures, encompassing both batch processing (AWS Glue, Athena, EMR) and real-time streaming (Kinesis/Kafka, SQS/SNS).
• Architect solutions using NoSQL databases including Amazon DynamoDB and MongoDB, selecting appropriate data storage patterns based on access patterns and scale.
• Apply best practices in data modelling, partitioning, and query optimisation across relational, NoSQL, and warehouse layers.

• Security, Compliance & Governance

• Ensure all solutions adhere to enterprise security, compliance, and governance frameworks within a highly regulated industry.
• Integrate Veracode and other SAST/DAST tooling into the development lifecycle to proactively identify and remediate security vulnerabilities.
• Design and implement data encryption strategies at rest and in transit, leveraging AWS KMS, TLS/SSL, and secrets management tools (AWS Secrets Manager, Parameter Store).
• Apply secure-by-design principles across all architectural decisions, including API security, identity federation, and zero-trust networking.
• Maintain deep understanding of communication protocols (REST, GraphQL, gRPC) to make informed integration and interoperability decisions.

• Engineering Excellence & POC Delivery

• Lead significant Proof of Concept (POC) and Proof of Value (POV) engagements, validating architectural approaches and emerging technologies ahead of production commitment.
• Operate comfortably across the full developer lifecycle — authoring requirements, documenting architectural patterns, writing production-quality code, defining tests, and deploying to cloud environments.
• Champion DevOps and automation practices including CI/CD pipeline design, Infrastructure as Code (IaC)using Terraform or AWS CDK, and observability/monitoring frameworks.
• Collaborate closely with development teams, third-party suppliers, and product stakeholders to ensure alignment with architectural principles and delivery objectives.
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• Implement robust authentication and authorisation mechanisms for MCPs, AI Agents, and APIs, ensuring compliance with enterprise security standards (OAuth 2.0, API Gateway policies, IAM roles).
• Evaluate and recommend AI frameworks, agent orchestration tools, and emerging GenAI technologies to continuously advance platform capability.

Qualifications

• Proven experience as a Senior Solution Architect or equivalent in a large-scale, regulated enterprise environment.
• Deep hands-on expertise with AWS (EC2, S3, Lambda, Glue, Athena, Kinesis, SNS, SQS, Redshift, DynamoDB, API Gateway, IAM, KMS).
• Demonstrated experience designing and deploying AI/ML and GenAI applications on AWS.
• Hands-on experience building and deploying MCP servers and AI Agents, with a strong understanding of agent orchestration patterns and tool-use protocols.
• Strong knowledge of API authentication and security — OAuth 2.0, OpenID Connect, JWT, API Gateway authorisers, mTLS.
• Experience designing batch and streaming data pipelines at enterprise scale.
• Working knowledge of NoSQL databases (DynamoDB, MongoDB) and Data Warehouse technologies (Redshift, Snowflake, or equivalent).
• Familiarity with Veracode or equivalent security vulnerability scanning tools integrated into CI/CD pipelines.
• Strong understanding of data encryption principles, key management, and compliance-driven data handling.
• Proficiency with IaC tools (Terraform, AWS CDK, or CloudFormation) and CI/CD platforms (Jenkins, GitHub Actions, or equivalent).

• Nice to Have

• Experience with multi-agent frameworks (LangGraph, AutoGen, CrewAI, or similar).
• Knowledge of data mesh or data fabric architectural patterns.
• Familiarity with vector databases (Pinecone, OpenSearch, pgvector) for RAG-based AI architectures.
• AWS certifications (Solutions Architect Professional, Data Engineer, or AI/ML Specialty).

Additional Information

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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