Sr. AI Engineer, AI FDE
New
J
JobgetherAI and machine learning
Remote work opportunity based in India.Full-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- AWSGCPMicrosoft AzureGenerative AILangChain
Requirements
- Extensive hands-on industry experience in data science, machine learning, and developing practical AI solutions.
- Demonstrated experience building generative AI applications, including RAG pipelines, multi-agent systems, Text-to-SQL solutions, and fine-tuned models.
- Familiarity with AI development frameworks and tools such as Hugging Face, LangChain, and DSPy.
- Expertise in deploying production-grade generative AI applications, including evaluation methodologies, performance optimization, and operational reliability.
- Experience building and deploying machine learning solutions on AWS, Microsoft Azure, or Google Cloud Platform.
- Proficiency with pandas, scikit-learn, and PyTorch.
- A graduate degree in a quantitative field such as computer science, engineering, statistics, or operations research, or equivalent practical experience.
- Strong communication and presentation skills, including explaining and teaching complex technical concepts to technical and non-technical audiences.
- Willingness to travel periodically to meet customers and support project delivery.
- Preferred: experience with large-scale distributed data processing using Apache Spark and the Databricks Intelligence Platform.
Responsibilities
- Design and develop generative AI solutions using RAG, multi-agent systems, Text-to-SQL, and model fine-tuning.
- Lead the deployment and production rollout of customer-facing and internal AI applications.
- Ensure AI applications are reliable, scalable, and performant.
- Advise customers and translate business challenges into AI architectures and implementation strategies.
- Test, evaluate, and optimize production-grade AI applications through performance analysis and iteration.
- Collaborate with product, engineering, research, and developer relations teams on product priorities and the technical roadmap.
- Share technical expertise through customer engagements, conference presentations, and internal knowledge-sharing.
- Support strategic projects and subject-matter experts with practical AI engineering expertise.
- Travel to customer locations approximately once every four to eight weeks, as business needs require.
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