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    Home/Jobs/Applied AI Engineer (Automation)

    Applied AI Engineer (Automation)

    Fusemachines

    United States
    3-8 years
    Today
    ₹15–28 LPA
    Full-time
    Remote

    Skills Required

    LLM
    RAG
    LangChain
    Agentic AI
    Gen AI
    OpenAI
    Python
    FastAPI
    n8n
    Make
    Zapier
    LangGraph
    Google ADK
    Pinecone
    Elasticsearch

    Description

    Fusemachines is a global AI strategy, talent, and education services provider focused on democratizing AI. The Applied AI Engineer (Automation) role involves delivering AI and automation solutions from prototype to production.

    Company: Fusemachines

    Role: Applied AI Engineer (Automation)

    Location: Remote

    Experience:

    • 3–8 years of software or AI engineering experience
    • 2–3+ years of AI Automation, Generative AI, or Agentic AI experience

    Key Skills:

    • Python
    • APIs
    • FastAPI
    • LLM platforms/APIs (OpenAI, IBM watsonx.ai, Amazon Bedrock)
    • Automation tools (n8n, Make, Zapier or similar)
    • LangChain
    • LangGraph
    • Google ADK
    • Vector databases (Pinecone, Elasticsearch, pgvector)
    • Graph databases
    • Docker
    • Cloud deployment (AWS, GCP, Azure, IBM)
    • Async/queuing patterns (Celery, Redis, Kafka)
    • RAG fundamentals
    • Retrieval systems

    Role Focus:

    • Design, develop, and deploy tailored AI and automation solutions aligned to client objectives
    • Translate business problems into production-grade AI workflows and services
    • Build and deploy agentic workflows including tool calling and structured outputs
    • Implement RAG pipelines using vector and graph databases
    • Ship prototypes and harden them into scalable, reliable, monitored production systems
    • Participate in discovery and run technical calls and demos
    • Communicate tradeoffs clearly to clients and internal stakeholders
    • Improve deployed solutions through feature work, bug fixes, monitoring, and prompt/model improvements
    • Produce clear technical documentation, client demos, and internal playbooks
    • Stay current on LLM tooling and delivery best practices

    Additional responsibilities:

    • Collaborate closely with Solutions Architects, Delivery/Engagement leads, and Product Managers
    • Operate in a client-facing environment

    Nice to have:

    • Experience with fine-tuning LLMs or other ML models
    • Broader ML exposure
    • Familiarity with observability and tracing tools (LangSmith, OpenTelemetry)
    • Prompt/version lifecycle management experience
    • Experience with graph databases and knowledge graphs
    • Familiarity with data governance and AI governance concepts including PII handling, auditability, access controls, and risk awareness
    • Prior consulting experience
    • Experience working in fast-paced startup environments

    Other:

    • Contracted role
    • Full-time
    • Fusemachines has offices in North America, Asia, and Latin America
    • Fusemachines serves industries such as retail, manufacturing, and government
    • Company mission to democratize AI and provide high-quality AI education in underserved communities

    Prepare for this role

    Recommended resources to build the skills for this position. Sponsored.

    Python for Everybody Specialization

    Coursera

    Learn Python from scratch — variables, data structures, web scraping, and databases.

    Generative AI with Large Language Models

    Coursera

    Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.

    Python 3 Programming Specialization

    Coursera

    Intermediate Python covering classes, inheritance, APIs, and data processing.

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