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- Tasks: Build and optimise high-performance data pipelines for AI/ML models in finance.
- Company: Join ARi, a leader in AI-powered financial risk management solutions.
- Benefits: Enjoy a hybrid work model, competitive salary, equity options, and professional growth opportunities.
- Why this job: Make a real impact on financial stability while working with cutting-edge technology in a collaborative culture.
- Qualifications: 5+ years in software/data engineering, strong Python skills, and experience with big data technologies required.
- Other info: Be part of a rapidly growing company focused on innovation and data security.
The predicted salary is between 48000 - 72000 £ per year.
22 hours ago Be among the first 25 applicants
Direct message the job poster from Artificial Risk Intelligence
CEO & Founder| We turn Risk Into Revenue|We Help CFO\’s and Risk Managers gain real-time insights into market volatility and credit exposures…
Job Title: Software/Data Engineer (AI/ML Infrastructure)
Company: Ari (Artificial Risk Intelligence)
Location: London, UK (Hybrid)
About ARi:
ARi is at the forefront of transforming financial risk management. We deliver cutting-edge AI-powered solutions that empower CFOs and Risk Managers with unparalleled insights into market volatility, credit exposures, and balance sheet optimisation. Our mission is to provide financial institutions with the most advanced, secure, and data-driven tools, built on a foundation of robust data integrity and privacy-by-design. We are committed to pushing the boundaries of financial AI with unwavering reliability and performance.
The Opportunity:
We are seeking a talented and driven Software/Data Engineer with a strong affinity for AI/ML infrastructure to join our growing engineering team. In this pivotal role, you will be instrumental in building, maintaining, and optimising the high-performance data infrastructure and sophisticated pipelines that feed our cutting-edge AI/ML models. You will work with complex, high-volume financial datasets, ensuring their quality, integrity, and security from raw ingestion to AI model consumption, and ultimately to secure client delivery.
If you are passionate about building scalable, secure data systems, adept at working with the latest ML infrastructure tools, and eager to contribute to a product that directly impacts financial stability and innovation, ARi is the place for you.
What You\’ll Do:
●Design & Build High-Performance Data Pipelines: Develop, optimise, and maintain robust ETL/ELT pipelines for ingesting, transforming, and loading large volumes of diverse financial data, specifically optimised for AI/ML training and inference.
●Architect Data for AI: Design and implement data schemas, feature stores, and data versioning strategies to ensure high-quality, consistent, and traceable data inputs for machine learning models.
●Strengthen MLOps Capabilities: Collaborate closely with AI/ML Engineers to build and maintain the infrastructure for seamless model deployment, monitoring (performance, drift, bias), retraining, and version control in production environments.
●Develop Core Microservices: Contribute to the design and development of critical backend services and APIs that power our balance sheet optimisation and financial risk management applications, ensuring high throughput and low latency.
●Cloud-Native Data Infrastructure: Collaborate on designing and optimizing scalable cloud-native data architectures (data lakes, data warehouses, streaming platforms) for performance, scalability, and cost-efficiency within AWS, Azure, or GCP.
●Enforce Security & Privacy by Design: Implement and adhere to the highest standards of data security (encryption, granular access controls, tokenization) and contribute to privacy-enhancing practices within data pipelines, especially when dealing with sensitive financial data for AI.
●Troubleshoot & Optimize: Proactively identify and resolve data-related issues and performance bottlenecks, implementing continuous improvements to data processes and infrastructure to meet real-time operational demands.
●Collaborate: Work cross-functionally with AI/ML Engineers, Product Managers, Financial Risk Analysts, and other stakeholders to deliver high-quality, impactful, and secure solutions.
What You\’ll Bring:
●5+ years of professional experience as a Software Engineer or Data Engineer, ideally within a FinTech, financial services, or highly regulated data-intensive AI environment.
●Strong proficiency in Python for data manipulation, scripting, backend development, and experience with its AI/ML ecosystem (e.g., Pandas, NumPy, scikit-learn, and familiarity with TensorFlow/PyTorch data pipelines).
●Expertise in SQL for complex data querying, analysis, and database management (relational and NoSQL).
●Proven experience with big data technologies such as Apache Spark, Kafka, Flink, or similar distributed processing and streaming frameworks.
●Solid understanding of cloud platforms (AWS, Azure, or GCP) including their AI/ML and data services (e.g., S3, EC2, Lambda, Data Lake, Databricks, Vertex AI, Azure ML, SageMaker).
●Hands-on experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes) for automating and managing the ML lifecycle.
●Proficiency in at least one modern backend language beyond Python, such as Go or Rust , for building high-performance, concurrent, and secure microservices. (C++ for specific high-performance data processing or PETs integration is a plus).
●Strong understanding of data warehousing concepts (e.g., Snowflake, Redshift, BigQuery) and advanced data modeling.
●Deep knowledge of cybersecurity principles related to data at rest and in transit, identity and access management (IAM), and secure coding practices within data pipelines.
●Familiarity with financial data (e.g., market data, loan books, transaction data) and/or financial risk management concepts is a significant advantage.
●Bachelor\’s or Master\’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related technical field.
● Strong problem-solving skills, meticulous attention to detail, and excellent collaboration abilities within an agile team.
Why Join ARi?
●Transformative Impact: Directly contribute to the financial stability and operational efficiency of leading global financial institutions through cutting-edge AI.
●Pioneer Innovation: Work at the intersection of advanced AI, high-performance data engineering, and cutting-edge privacy-enhancing technologies.
●Accelerated Growth: Be part of a dynamic, rapidly expanding, and well-funded company with excellent opportunities for professional development and career advancement.
●Collaborative Culture: Join an intellectually stimulating, supportive, and truly collaborative team dedicated to solving complex problems.
●Competitive Package: Attractive salary, equity options, and a comprehensive benefits package.
Ready to engineer the data backbone of secure financial AI?
Send CV\’s and Contact:
gibran@artificialriskintelligence.net
#DataEngineer #SoftwareEngineer #AI #MachineLearning #MLOps #FinTech #FinancialRisk #BigData #CloudEngineering #Python #GoLang #RustLang #SQL #LondonTech #Hiring #DataPipelines #Cybersecurity #AIInfrastructure
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Software/Data Engineer (AI/ML Infrastructure) employer: Artificial Risk Intelligence
Contact Detail:
Artificial Risk Intelligence Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software/Data Engineer (AI/ML Infrastructure)
✨Tip Number 1
Familiarise yourself with the specific AI/ML tools and technologies mentioned in the job description, such as TensorFlow, PyTorch, and MLOps tools like MLflow and Kubeflow. Being able to discuss your hands-on experience with these tools during an interview will demonstrate your readiness for the role.
✨Tip Number 2
Network with professionals in the FinTech and AI sectors, especially those who work at ARi or similar companies. Engaging with them on platforms like LinkedIn can provide you with valuable insights into the company culture and expectations, which can be beneficial during interviews.
✨Tip Number 3
Prepare to discuss real-world examples of how you've built and optimised data pipelines or worked with big data technologies. Having concrete examples ready will help you illustrate your problem-solving skills and technical expertise effectively.
✨Tip Number 4
Stay updated on the latest trends in financial risk management and AI technologies. Being knowledgeable about current developments in these areas will not only impress your interviewers but also show your genuine interest in the field and the company's mission.
We think you need these skills to ace Software/Data Engineer (AI/ML Infrastructure)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in software and data engineering, particularly in AI/ML infrastructure. Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for financial risk management and AI technologies. Mention specific projects or experiences that align with ARi's mission and the responsibilities of the role.
Showcase Technical Skills: Clearly outline your technical skills, especially in Python, SQL, and big data technologies. Provide examples of how you've used these skills in previous roles to solve complex problems or improve processes.
Highlight Collaboration Experience: Since the role involves working cross-functionally, emphasise any past experiences where you collaborated with different teams, such as AI/ML engineers or product managers, to deliver successful projects.
How to prepare for a job interview at Artificial Risk Intelligence
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and big data technologies. Highlight specific projects where you've built data pipelines or worked with AI/ML infrastructure, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Mission
Familiarise yourself with ARi's focus on transforming financial risk management through AI. Be ready to explain how your skills can contribute to their mission of providing advanced, secure, and data-driven tools for financial institutions.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice explaining your thought process when troubleshooting data-related issues or optimising performance in data pipelines, as this is crucial for the role.
✨Demonstrate Collaboration Skills
Since the role involves working cross-functionally, be ready to share examples of how you've successfully collaborated with other teams, such as AI/ML engineers or product managers, to deliver impactful solutions.
