Senior Software Engineer
About The Position
Wellington Management is seeking a Senior Software Engineer to design and deliver AI-enabled software solutions that directly support their Investment and Research teams. This role focuses on building robust, production-grade backend systems and platforms that integrate advanced analytics and AI capabilities into investment workflows. The engineer will be hands-on, 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.
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 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).
Nice To Haves
- Experience with Azure is a plus.
- 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.
- 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.
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.
Benefits
- retirement plan
- health and wellbeing
- dental
- vision
- pharmacy coverage
- health savings account
- flexible spending accounts
- commuter program
- employee assistance program
- life and disability insurance
- adoption assistance
- back-up childcare
- tuition/CFA reimbursement
- paid time off (leave of absence, paid holidays, volunteer, sick and vacation time)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
