Senior Software Engineer

About the role

Wellington Management offers comprehensive investment management capabilities that span nearly all segments of the global capital markets. Our investment solutions, tailored to the unique return and risk objectives of institutional clients in more than 60 countries, draw on a robust body of proprietary research and a collaborative culture that encourages independent thought and healthy debate. As a private partnership, we believe our ownership structure fosters a long-term view that aligns our perspectives with those of our clients. Senior Software Engineer POSITION We are seeking a Senior Software Engineer to design and deliver AI-enabled software solutions that directly support our Investment and Research teams. This role is focused on building robust, production-grade backend systems and platforms that integrate advanced analytics and AI capabilities into investment workflows. You will serve as a hands-on engineer responsible for implementing and scaling applications that leverage modern AI technologies while adhering to high standards of reliability, security, and performance. The ideal candidate is a strong backend engineer with platform instincts, capable of translating ambiguous business problems into well-designed systems and production-ready software. This is a high-impact role at the intersection of engineering, data, and investment research.

Responsibilities

• Implementation of AI-enabled applications and services supporting investment and research workflows.
• Build and maintain scalable backend systems, APIs, and data pipelines that integrate AI models, LLMs, and analytics services into business processes.
• Implement cloud-native systems on AWS, ensuring strong security, scalability, cost efficiency, and operational resilience.
• Follow engineering best practices including CI/CD, automated testing, observability, infrastructure-as-code, and documentation standards.
• Participate in technical design discussions, conduct code reviews to elevate overall code quality and system design maturity.
• Evaluate and incorporate emerging AI technologies (e.g., LLMs, retrieval-augmented generation, model APIs, vector databases) where appropriate, with careful attention to governance, explainability, and limitations.
• Improve and modernize existing platforms to increase performance, maintainability, and extensibility.
• Collaborate with data engineering and infrastructure teams to ensure seamless integration across systems.

Requirements

• 5-10+ years of professional software engineering experience, with a strong focus on backend systems and platforms.
• Proven experience building and operating production-grade applications and platforms in Python (preferred), or similar backend languages.
• Deep understanding of API design
• Hands-on experience with AWS services such as EC2, ECS, Lambda, S3, DynamoDB, CloudWatch, IAM, and CloudFormation or Terraform. Experience with Azure is a plus.
• Experience integrating AI/ML capabilities into production systems, including: Working with LLM APIs and prompt engineering.
• Retrieval systems (e.g., vector databases).
• Model evaluation, monitoring, and governance considerations.
• Strong knowledge of data storage technologies (relational and NoSQL), caching layers, and performance optimization techniques.
• Familiarity with containerization (Docker) and orchestration platforms (ECS, EKS, or Kubernetes).
• Exposure to frontend technologies (e.g., React, TypeScript) is a plus, but not required.
• Experience in financial services, asset management, or capital markets is strongly preferred.
• Preferred Attributes
• Strong systems thinking and architectural rigor.
• Ability to operate effectively in ambiguous, research-driven environments.
• Clear communicator capable of bridging technical and investment domains.
• High standards for code quality, documentation, and operational excellence.
• Pragmatic approach to applying AI-balancing innovation with reliability, compliance, and risk management.

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