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Senior AI Software Engineer

Posted 27 days agoViewed

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💎 Seniority level: Senior, 5+ years

📍 Location: United States

🔍 Industry: Software Development

🏢 Company: MNTN👥 251-500💰 $2,000,000 Seed over 2 years agoAdvertisingReal TimeMarketingSoftware

🗣️ Languages: English

⏳ Experience: 5+ years

🪄 Skills: DockerPostgreSQLPythonSQLArtificial IntelligenceCloud ComputingGitKubernetesMachine LearningAlgorithmsData StructuresCommunication SkillsAnalytical SkillsCI/CDProblem SolvingRESTful APIsSoftware Engineering

Requirements:
  • 5+ years of professional software engineering experience, demonstrating strong organizational skills and a track record of delivering reliable, high-quality code.
  • Proficiency in modern AI frameworks and workflows—experience with tools like ChatGPT, Claude, Copilot, Cursor, or similar. (No multi-year requirement needed, but proven proficiency is essential.)
  • Experience with orchestrating LLMs and AI pipelines (e.g., LangChain or similar orchestration libraries).
  • Experience with vector databases (e.g., Pinecone, Chroma, Weaviate, Milvus) and integrating them into AI-driven applications.
  • Hands-on experience with SQL data storage and processing (PostgreSQL preferred).
  • Solid understanding of cloud infrastructure, including containerization (Docker) and orchestration (Kubernetes).
  • Strong proficiency with version control (Git), CI/CD pipelines, and automated testing practices.
  • Excellent problem-solving and communication skills, with the ability to articulate AI-driven solutions to both technical and non-technical audiences.
  • Ability to orchestrate new codebases with AI to ensure accuracy, reliability, and alignment with business goals.
  • A track record of translating business requirements into successful AI-powered solutions, from concept to production.
Responsibilities:
  • Design and build AI-powered solutions that enhance automation, analytics, and decision-making.
  • Develop orchestration and agent-based workflows using modern AI frameworks (e.g., LangChain) to handle repetitive tasks like data analysis.
  • Integrate and optimize Large Language Models (LLMs) for various use cases, ensuring efficient prompts, context handling, and output evaluation.
  • Leverage vector databases (e.g., Pinecone, Weaviate, Milvus, Chroma) and relevant tooling to power advanced search, retrieval, and recommendation systems.
  • Collaborate with cross-functional teams, effectively translating complex AI concepts for both technical and non-technical stakeholders.
  • Continuously enhance and refine AI models, pipelines, and systems to improve efficiency, scalability, and reliability.
  • Implement best practices for version control, CI/CD, and testing to maintain high-quality AI-driven solutions.
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