Staff Software Engineer (AI)
United StatesFull-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 8+ years
- Required Skills
- AWSDockerPythonDjangoKubernetesTypeScriptFastAPIReactCI/CDRESTful APIsDevOpsPrompt EngineeringMLOpsDistributed Systems
Requirements
- 8+ years of experience in software engineering with cross-team architectural influence
- Proven experience delivering AI-powered or GenAI-based production systems
- Strong proficiency in Python and RESTful API development (e.g., FastAPI or Django)
- Experience with LLM integrations, RAG pipelines, prompt engineering, or evaluation frameworks
- Solid understanding of distributed systems, cloud-native architecture, and scalable backend systems
- Familiarity with AWS or similar cloud platforms and modern DevOps practices (CI/CD, Docker, Kubernetes)
- Experience with vector databases and semantic search technologies (e.g., Pinecone, pgvector, OpenSearch)
- Knowledge of MLOps/LLMOps concepts, model lifecycle, and production deployment practices
- Ability to write architectural documentation (RFCs, ADRs) and communicate across technical and non-technical audiences
- Experience mentoring engineers and contributing to engineering culture and standards
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
Responsibilities
- Own and define the reference architecture for AI platform systems, including APIs, RAG pipelines, vector retrieval, and model serving infrastructure
- Lead design standards, architectural reviews, and build-vs-buy decisions across AI and platform components
- Develop and maintain scalable data pipelines and infrastructure supporting production AI services
- Design and implement backend services in Python and REST APIs, with occasional full-stack contributions (React/TypeScript)
- Build evaluation frameworks, observability systems, and performance monitoring for AI models and services
- Integrate and manage LLM-based systems, including prompt management, response validation, and fallback strategies
- Ensure compliance and security by design, collaborating with security teams on governance and regulatory requirements
- Mentor engineers, lead technical discussions, and promote engineering excellence across teams
- Partner with product and engineering leadership to define AI roadmap and platform evolution
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