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 is focused on building robust, production-grade backend systems and platforms that integrate advanced analytics and AI capabilities into investment workflows. The engineer will be responsible for implementing and scaling applications that leverage modern AI technologies while adhering to high standards of reliability, security, and performance. 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
