Senior Backend Engineer, AI Team
J
JobgetherFinancial Services, AI
Based in the United StatesFull-TimeSenior
Salary$184,500–$217,100 per year
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Job Details
- Experience
- 5+ years of total software engineering experience, including 3+ years working in artificial intelligence, data science, or machine learning engineering.
- Required Skills
- AWSPythonKubernetesMachine LearningPyTorchPandasLLMGenerative AILangChain
Requirements
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Statistics, or another STEM-related discipline.
- 5+ years of total software engineering experience, including 3+ years working in artificial intelligence, data science, or machine learning engineering.
- 3+ years of experience with modern cloud and data technologies such as AWS, Amazon Bedrock, SageMaker, Databricks, or Kubernetes.
- Strong foundational knowledge of generative AI, transformers, LLM fine-tuning, search and ranking, retrieval-augmented generation (RAG), and LLM-based agents.
- Experience tuning neural networks using custom datasets and developing or improving machine learning models.
- Hands-on experience with technologies and frameworks such as Hugging Face, LangChain, and chatbot development platforms.
- Strong programming and analytical capabilities, particularly with Python and tools such as PyTorch, Pandas, NumPy, and Scikit-learn.
- Ability to analyze complex technical systems, identify root causes, and translate AI capabilities into practical, scalable products.
- Strong collaboration and communication skills, with the ability to work effectively across technical and non-technical teams.
- A high degree of ownership, precision, curiosity, and drive, combined with enthusiasm for building innovative products and creating meaningful customer impact.
- A growth-oriented and optimistic mindset, with a willingness to learn quickly and adapt in a fast-changing AI and technology environment.
Responsibilities
- Contribute to the design, development, and deployment of customer-facing AI products, including an AI-powered virtual support agent.
- Review proprietary datasets, vector database architecture, data pipelines, and supporting tools to identify gaps, improve quality, and strengthen system performance.
- Debug, enhance, and optimize AI and machine learning models while helping scale data and inference pipelines for production environments.
- Apply modern generative AI techniques, including retrieval-augmented generation, LLM agents, search and ranking improvements, and model fine-tuning, to solve complex customer and business problems.
- Collaborate with product, engineering, data science, and other cross-functional stakeholders to align AI initiatives with strategic and customer-focused objectives.
- Establish scalable monitoring and operational processes to maintain the reliability, quality, and performance of AI systems.
- Help define and execute a roadmap for AI innovation, identifying opportunities to leverage emerging technologies and improve existing products.
- Mentor and support junior team members while contributing to a culture of technical excellence, experimentation, and continuous improvement.
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