Location
Remote/Hybrid
Seniority
Senior · 5+ years exp
Overview
Company
Impact
Profile match
Cognium is an AI-powered wealth management platform that automates portfolio monitoring, risk analysis, recommendations, compliance checks, and advisor workflows to help wealth managers scale efficiently.
We're looking for a Full-Stack Engineer who's comfortable owning a feature from idea to production: designing the data model, building the API, and shipping a polished UI. You'll work closely with product, design, and our AI engineering team to bring new capabilities to life across the stack.
Responsibilities:
- Design, build, and ship features across the full stack from database schema and backend services to frontend UI.
- Build and maintain RESTful APIs that power our web application and integrations.
- Develop responsive, accessible, and performant user interfaces using modern frontend frameworks.
- Collaborate with product and design to turn requirements into technical specs and shippable increments.
- Write clean, well-tested, maintainable code, and participate actively in code review.
- Improve application performance, reliability, and security across the stack.
- Work with our AI engineering team to integrate AI-powered features into user-facing product surfaces.
- Contribute to architecture decisions, tooling, and engineering best practices as the team and product scale.
- Monitor, debug, and resolve production issues, and contribute to on-call rotations as needed.
Requirements:
- 5+ years of professional experience building full-stack web applications in production.
- Strong frontend skills: TypeScript and React, with experience building production-grade UIs.
- Strong backend skills: Python (FastAPI, Django, or similar), with experience designing and building APIs and services.
- Practical experience designing and working with relational databases (PostgreSQL, MySQL) and writing efficient queries.
- Experience building and consuming REST APIs.
- Experience integrating AI/LLM-powered features into a product by calling LLM APIs, working with retrieval-augmented generation (RAG) or vector search, or partnering with ML/AI teams to ship model-backed functionality.
- Familiarity with cloud infrastructure (Azure, AWS, or GCP), CI/CD pipelines, and containerization (Docker).
- Strong understanding of software engineering fundamentals: testing, version control, code review, and system design.
- Proficiency working with AI coding assistants (e. g., Claude Code, GitHub Copilot, Cursor) to accelerate development, while critically reviewing and validating AI-generated code.
- Comfort working in a remote, async-first environment with strong written communication skills.
Nice to Have:
- Familiarity with infrastructure-as-code (Terraform) and observability tooling (Datadog, Grafana, Sentry).
- Familiarity with vector databases or embedding-based search for AI-powered features.
- Background working in a startup or small, cross-functional team.
- Exposure to design systems and component libraries.
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