We are seeking an experienced and highly motivated Senior AI Engineer with 10+ years of professional experience in enterprise AI/ML engineering, intelligent automation, and large-scale platform environments. The role focuses on designing, developing and deploying scalable AI-first solutions supporting supply chain finance, trade ecosystems, logistics intelligence and operational decisioning within the Banking \& Financial Services industry.
The ideal candidate will possess strong expertise in AI/ML engineering, distributed systems, cloud-native platforms, and real-time transaction processing, combined with practical experience in Supply Chain Finance (SCF), Trade Finance, logistics workflows and enterprise transaction ecosystems.
The role is primarily focused on AI/ML platform engineering and intelligent enterprise automation within mission-critical financial and operational environments.
Key Responsibilities
- Design, build and optimize scalable AI and machine learning solutions for enterprise-grade applications.
- Develop intelligent algorithms and data pipelines for extraction, transformation, and loading of large volumes of structured and unstructured real-time data.
- Deploy AI/ML solutions from experimental and theoretical data science models into production-ready enterprise platforms.
- Build predictive analytics, anomaly detection, forecasting and intelligent automation capabilities supporting trade processing, supply chain finance, logistics intelligence, procurement ecosystems and operational optimization.
- Run experiments, benchmark model performance, conduct validation testing and continuously improve deployed models and AI workflows.
- Identify, troubleshoot and resolve model drift, performance bottlenecks, scalability challenges and deployment issues.
- Build and maintain scalable ML pipelines, model governance frameworks, and AI lifecycle management processes.
- Collaborate closely with business stakeholders, enterprise architects, product teams, data scientists and engineering groups.
- Work with cloud-native and enterprise software platforms where AI/ML models are deployed.
- Contribute to architecture discussions, technical strategy and enterprise AI engineering best practices.
- Mentor junior engineers and support cross-functional innovation initiatives.
Platform \& Engineering Responsibilities
- Support the operational excellence and reliability of enterprise AI and transaction platforms with strict uptime, scalability and data integrity requirements.
- Oversee high-throughput distributed systems built on Java, Spring Boot, Kafka, MQ and microservices architectures.
- Ensure performance and integrity of enterprise data platforms including Oracle DB, MongoDB, Redis and Graph databases.
- Manage cloud-native deployment environments across AWS, Azure and GCP with Kubernetes (K8s)-based orchestration.
- Oversee secure deployment practices, CI/CD pipelines, platform optimization and infrastructure scalability initiatives.
- Support platform modernization initiatives balancing legacy application maintenance with modern microservices transformation.
- Drive security-first engineering practices including vulnerability remediation and secure coding standards using tools such as Fortify and SonarQube.
Required Skills \& Experience
- 10+ years of experience in enterprise software engineering, AI/ML engineering, platform engineering, or large-scale distributed systems environments.
- Strong experience within FinTech, Banking, Supply Chain Finance (SCF), Trade Finance, logistics platforms, or enterprise transaction ecosystems.
- Deep understanding of trade digitization workflows, financial messaging (MT/MX), accounting entries, and transaction processing systems.
- Experience with MLOps, model lifecycle management, AI deployment pipelines and model monitoring frameworks.
- Exposure to Generative AI, LLM integrations, intelligent automation platforms, or AI-driven enterprise workflows is desirable.
Preferred Domain Experience
Candidates with prior experience in one or more of the following domains will be highly preferred:
- Supply Chain Finance (SCF)
- Global Trade \& Trade Finance
- Logistics Intelligence \& Trade Operations
- Procurement \& Transaction Ecosystems
- Enterprise Financial Messaging Platforms
- Distribution \& Supply Network Visibility
- Enterprise Transaction Processing Platforms
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related disciplines.
- Experience working in large enterprise or multinational environments.
- Exposure to AI-driven decisioning platforms and intelligent enterprise automation frameworks is an advantage.
Key Attributes
- Strong analytical and problem-solving mindset.
- Excellent communication and stakeholder management capabilities.
- Ability to operate effectively in fast-paced enterprise environments.
- Passion for innovation, optimization and business-focused AI solutions.
- Strong ownership mindset with focus on scalability, reliability, and engineering excellence.