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AI Software Engineer

Nexorant LLCUnited States🇺🇸United StatesPosted Oct 7, 2026

Why This Role Stands Out

Advance your career by building cutting-edge AI applications and services in a hybrid environment that fosters collaboration and innovation. If you have a strong foundation in Python and experience with Generative AI, LLMs, and RAG, you'll thrive in this role, contributing to impactful solutions and continuous learning. Apply today to join a dynamic team and shape the future of AI technology.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
21 hours ago
DockerSQLAWSMachine LearningScikit-learnAzureGenerative AIGitGoogle CloudLLMPyTorchPythonRESTTensorFlow

Job Description

Job Summary

We are seeking an AI Software Engineer with 1–3 years of experience to design, develop, and deploy software solutions powered by artificial intelligence and machine learning. The role will involve building AI-enabled applications, integrating machine learning models and APIs, developing data-processing pipelines, and working with engineering teams to deliver scalable and reliable AI solutions.

The ideal candidate should have strong programming skills, practical experience with Python and modern AI/ML frameworks, and an understanding of generative AI, APIs, data processing, and software development practices.

Responsibilities

  • Design, develop, test, and maintain AI-powered software applications.
  • Build and integrate machine learning and generative AI capabilities into production applications.
  • Develop Python-based services, APIs, and backend components for AI solutions.
  • Work with large datasets for data preparation, processing, validation, and analysis.
  • Integrate LLMs, AI APIs, and machine learning models into applications.
  • Develop and optimize prompts for LLM-based applications and AI workflows.
  • Build AI features such as conversational interfaces, document processing, recommendation systems, classification, and information extraction.
  • Work with structured and unstructured data to support AI/ML applications.
  • Develop data and model pipelines for training, evaluation, and deployment.
  • Evaluate AI/ML model performance and identify opportunities for improvement.
  • Implement testing, monitoring, logging, and performance optimization for AI applications.
  • Collaborate with software engineers, data scientists, product managers, and business stakeholders.
  • Participate in code reviews and follow software engineering best practices.
  • Troubleshoot production issues and improve application reliability and scalability.
  • Document technical designs, APIs, workflows, and AI solutions.
  • Stay current with emerging AI, machine learning, and generative AI technologies.

Qualifications

  • 1–3 years of professional software development experience with exposure to AI/ML.
  • Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field.
  • Strong programming experience with Python.
  • Good understanding of data structures, algorithms, object-oriented programming, and software development principles.
  • Experience with machine learning or AI frameworks such as PyTorch, TensorFlow, or scikit-learn.
  • Experience working with REST APIs and third-party AI/ML services.
  • Understanding of Generative AI and Large Language Models (LLMs).
  • Experience with Git and standard software development workflows.
  • Strong debugging, problem-solving, and analytical skills.
  • Ability to work effectively in a collaborative engineering environment.

Preferred Qualifications

  • Experience with OpenAI, Azure OpenAI, AWS Bedrock, Google Gemini, or similar AI platforms.
  • Experience building RAG (Retrieval-Augmented Generation) applications.
  • Familiarity with vector databases such as Pinecone, Weaviate, FAISS, or Chroma.
  • Experience with LangChain, LlamaIndex, or similar AI application frameworks.
  • Knowledge of prompt engineering and LLM evaluation.
  • Experience with Docker and cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Familiarity with CI/CD and DevOps practices.
  • Knowledge of SQL and NoSQL databases.
  • Experience with model deployment, monitoring, and optimization.

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