About the Role

We are seeking an AI Engineer to design, build, and deploy AI-powered solutions that enhance automation, compliance, and decision-making in the financial services sector. This role will focus on unstructured data use cases such as document intelligence, anomaly detection, and predictive analytics, leveraging cloud-native tools and platforms.

This position is highly impactful enabling clients to improve operational efficiency, strengthen regulatory compliance, and enhance data quality in tightly governed environments.

What You’ll Do

• Implement AI/ML models for processing operational data, including unstructured formats such as PDFs, documents, and emails.
• Build and deploy NLP, classification, and extraction models using cloud-based pipelines.
• Collaborate with product owners and business analysts to translate business problems into AI-driven solutions.
• Integrate AI capabilities into existing platforms and workflows via APIs and containerized services.
• Monitor, retrain, and manage model lifecycle using MLOps best practices.
• Apply AI techniques such as OCR and Intelligent Document Processing (IDP) to financial documents (e.g., fund prospectuses, investor reports, KYC/AML data).
• Ensure AI systems adhere to compliance, audit, and explainability requirements in regulated environments.
• Partner with engineering and data teams to align AI models with ETL/ELT workflows, data lakes, and structured/unstructured data handling.

Who You Are

We’re looking for experienced professionals with the following:

• 5+ years of experience in AI/ML engineering, applied machine learning, or data science.
• Proven track record deploying ML solutions in financial services, ideally in fund administration or asset management.
• Proficiency in Python (NumPy, Scikit-learn, PyTorch, Hugging Face), SQL, and Shell scripting.
• Strong expertise in AWS cloud services (e.g., Bedrock, SageMaker, Textract, Comprehend, Lambda, Step Functions, API Gateway).
• Hands-on experience with CI/CD pipelines for ML (GitHub Actions or similar).
• Familiarity with regulatory and compliance requirements (GDPR, MiFID II, AIFMD, SFDR) and their impact on AI systems.
• Exposure to financial data formats and regulatory reporting challenges.
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
• Certifications such as AWS Machine Learning Specialty or equivalent are a strong plus.
• Excellent communication skills with the ability to explain complex AI concepts to non-technical stakeholders.
• Collaborative, detail-oriented, and motivated by experimentation and continuous improvement.