A leading Investment Bank is investing heavily in next-generation AI capabilities to transform how knowledge, data, and insights are generated, consumed, and delivered across the organization.
This team is seeking a Senior Applied AI Engineer to partner directly with business stakeholders, technology teams, and end users to identify opportunities, rapidly develop solutions, and drive adoption of emerging AI technologies. The role is ideal for someone who enjoys working at the intersection of engineering, machine learning, and business engagement while operating in a highly collaborative and fast-paced environment.
Key Responsibilities:
- Partner with business leaders and end users to identify opportunities for AI-driven process improvement and automation.
- Design, develop, and deploy AI, machine learning, and intelligent workflow solutions from concept through production.
- Translate business requirements into scalable technical architectures and working prototypes.
- Build cloud-native applications and services that support data-intensive and AI-enabled workflows.
- Collaborate with platform and engineering teams to productionize successful proof-of-concepts.
- Establish best practices around system reliability, observability, monitoring, and operational support.
- Communicate complex technical concepts to both technical and non-technical stakeholders.
Required Qualifications:
- 5+ years of software engineering experience within enterprise technology environments.
- Advanced Python development experience with strong object-oriented programming skills.
- Experience with Java, C++, C#, or another object-oriented programming language.
- Strong understanding of software architecture, distributed systems, and engineering best practices.
- Experience designing and deploying solutions on public cloud platforms.
- Hands-on experience building AI, machine learning, generative AI, or intelligent automation solutions.
- Demonstrated ability to take ideas from initial discovery through prototype development and business adoption.
- Strong stakeholder management and communication skills.
- Experience supporting applications in complex production environments.
- Excellent analytical, troubleshooting, and problem-solving capabilities.
Preferred Qualifications:
- Experience developing LLM's, retrieval-based, or AI-assisted workflow applications.
- Knowledge of modern data architecture and large-scale data platforms.
- Experience with containerization and orchestration technologies such as Kubernetes.
- Familiarity with API design, microservices architecture, and distributed systems.
- Exposure to financial services, research, analytics, data products, or knowledge-management platforms.
- Cloud certifications across architecture, machine learning, or data engineering disciplines.
This opportunity offers the chance to help shape the future of AI adoption within a highly visible enterprise environment while working on business-critical initiatives with meaningful impact.
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