About Us

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.

About the Role

Lead Software Engineer

POSITION

We are seeking a Lead 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 senior technical leader and hands-on engineer responsible for architecting, 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

• Lead the architecture, design, and 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.

• Partner directly with investment professionals, research analysts, and product stakeholders to translate complex domain requirements into robust technical solutions.

• Design cloud-native systems on AWS, ensuring strong security, scalability, cost efficiency, and operational resilience.

• Establish engineering best practices including CI/CD, automated testing, observability, infrastructure-as-code, and documentation standards.

• Drive technical design discussions, conduct code reviews, and mentor engineers 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.

• Provide strong leadership and mentorship of other members of the team

Qualifications

• 8–12+ 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 (REST/GraphQL), microservices architecture, event-driven systems, and asynchronous processing patterns.

• 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.

• Experience implementing CI/CD pipelines and infrastructure-as-code using modern DevOps tooling.

• 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.

• Demonstrated ability to lead technical delivery, mentor engineers, and influence architectural direction.

Preferred Attributes

• Strong systems thinking and architectural rigor.

• Ability to operate effectively in ambiguous, research-driven envi