Senior Full Stack - Developer - AI Platform​/Onsite Mandatory​/Local to VA , DC and MD

Senior Full Stack Developer

Role Description

Key Responsibilities

• Design, develop, and maintain full stack web applications that integrate AI/ML models, knowledge graphs, and search interfaces for financial research.
• Build modern, responsive UIs using React.js (or equivalent) with a focus on usability and performance.
• Develop scalable, secure backend services using Python (FastAPI/Flask/Django), Node.js, or similar, including REST and GraphQL APIs.
• Integrate front-end components with AI/LLM services (e.g., GPT, Claude), document processing APIs, and financial datasets.
• Collaborate with Dev Ops and Cloud teams to deploy applications using CI/CD pipelines, containers (Docker), and orchestration (Kubernetes).
• Ensure production-grade observability, logging, and monitoring of full stack components.
• Work alongside data scientists and ML engineers to embed AI capabilities into end-user applications.
• Collaborate with UX teams to translate user feedback from investment professionals into intuitive features.
• Contribute to code reviews, design discussions, and agile ceremonies.
• Follow best practices in secure coding, data access control, and compliance (especially for financial systems).
• Ensure all code aligns with Carlyle's enterprise architecture, data governance, and cybersecurity policies.

Required Qualifications

• 5+ years of professional experience as a full stack or software engineer building enterprise-grade web applications.
• Expertise in:
  Frontend:
  React.js, Type Script, Redux, Tailwind/CSS-in-JS Backend:
  Python (FastAPI, Flask, Django), Node.js or similar Database:
  PostgreSQL, MongoDB, or graph/semantic databases (e.g., Neo4j, Amazon Neptune) Cloud: AWS preferred (Lambda, ECS, S3, API Gateway, Sage Maker a plus) Version Control & CI/CD:
  Git, Jenkins/Git Hub Actions
• Strong understanding of integrating AI/ML APIs and handling large volumes of financial and textual data.
• Familiarity with RESTful APIs, GraphQL, and microservices-based architecture.
• Experience working in financial services, private equity, or asset management technology teams.
• Exposure to AI/ML, NLP, or LLM-based applications.
• Familiarity with vector databases, document search tools (e.g., Elasticsearch), and RAG (retrieval-augmented generation) workflows.
• Experience working in an Agile or Scrum environment.