Senior AI Engineer
New
J
JobgetherArtificial Intelligence
Fully remote work environment within the United States.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience in software engineering, applied AI, machine learning, or related technical roles.
- Required Skills
- AWSPythonGCPMachine LearningSoftware EngineeringLLMGenerative AI
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
- 5+ years of experience in software engineering, applied AI, machine learning, or related technical roles.
- 1+ year of recent experience designing and delivering production-grade generative AI solutions.
- Strong proficiency in Python.
- Experience building cloud-native applications on platforms such as AWS or GCP.
- Hands-on experience with modern AI systems, including LLMs, agents, retrieval-augmented generation (RAG), and AI workflow automation.
- Practical experience with prompt engineering, model evaluation, tool calling, and AI application debugging.
- Experience designing AI evaluation approaches using metrics, test datasets, human review, and error analysis.
- Strong understanding of software engineering principles including system design, testing, scalability, and maintainability.
- Experience working with relational and/or NoSQL databases.
- Hands-on experience with vector databases, embeddings, and semantic search solutions.
Responsibilities
- Design, build, deploy, and maintain production-ready generative AI, agentic AI, and machine learning applications.
- Develop AI solutions using large language models (LLMs), multimodal models, retrieval-augmented generation (RAG), structured extraction, classification, and workflow automation.
- Create evaluation strategies, testing frameworks, and monitoring approaches to measure AI system quality and continuously improve performance.
- Build reliable AI applications with strong observability, guardrails, scalability, and maintainability.
- Apply prompt engineering, tool calling, context management, model selection, and debugging techniques to optimize AI workflows.
- Develop retrieval-based AI solutions using vector databases, embeddings, and semantic search technologies.
- Collaborate with engineering, product, data, and operations teams to integrate AI capabilities into client and business systems.
- Translate business and user requirements into practical AI architectures and technical implementations.
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