AI and Data Solution Architect

• Shape enterprise architecture strategies for complex technology programs, aligning solutions with client blueprints and long-term objectives.
• Design secure, scalable data platforms and AI-driven analytical solutions for capital markets and financial services organizations.
• Translate complex business challenges into innovative technology solutions that deliver measurable business outcomes.
• Develop technology roadmaps by evaluating emerging technologies, platforms, infrastructure, and AI capabilities.
• Architect advanced data pipelines and ETL solutions using Python and PySpark across relational, warehouse, and cloud-native environments.
• Design and manage distributed data processing solutions using Hadoop, Cloudera, distributed file systems, and NoSQL databases.
• Apply AI-assisted development tools, CI/CD practices, and container orchestration to improve quality and accelerate delivery.
• Serve as a senior technical advisor, mentoring development teams and governing architecture and engineering best practices across transformation programs.

The Team

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients’ success. You’ll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client’s unique requirements.

Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

Required

• 6+ years of experience in IT architecture, systems design, or a related technical discipline, with experience delivering enterprise-scale data and/or AI solutions in complex environments.
• 6+ years of experience with distributed data platforms in the Hadoop ecosystem, preferably Cloudera, including HDFS, Hive, Pig, Sqoop, and MongoDB.
• Experience delivering AI and data architecture solutions within Financial Services, particularly Capital Markets, Fraud Detection, Risk Analytics, or Regulatory Reporting.
• Strong proficiency in Python and PySpark, including Pandas, NumPy, and Pydantic, as well as modern data architectures such as Lakehouse, Medallion, Kafka, Flink, Data Mesh, and OLAP/OLTP modeling.
• Hands-on experience designing enterprise Generative AI solutions, including RAG pipelines, LLM integration, prompt engineering, multi-agent workflows, and vector databases such as Pinecone, FAISS, or Azure AI Search.
• Experience with CI/CD, Git, Docker, and Kubernetes, along with the organizational skills to manage multiple workstreams, take ownership of complex challenges, and deliver under tight deadlines

Preferred

• Master’s degree in Computer Science, Data Science, Software Engineering, Mathematics, or a related quantitative discipline, and/or equivalent professional experience delivering enterprise AI and data solutions.
• Commercial & Strategic Vision: Familiarity with competitor technology products and services, with a deep understanding of how architectural specialisms contribute to commercial outcomes and Return on Investment (ROI).
• Cloud Platform & Infrastructure: Hands-on experience designing and deploying solutions on major cloud platforms (AWS, Azure, or GCP), including cloud-native data services (Databricks, Snowflake) and applying infrastructure engineering principles alongside software architecture.
• Project & Program Management: Experience managing and delivering complex, multi-workstream technology programs, including stakeholder management, resource planning, and milestone governance.
• Industry Certifications: Relevant certifications such as AWS Certified Data Analytics, Google Professional Data Engineer, Databricks Certified Associate, or equivalent cloud and data architecture qualifications.