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    Job · 14612090

    UPS logistics logo

    Senior AI Engineer – Python, RAG, Agentic AI, ADK, MCP, GCP, Vertex AI, IBM Watsox

    UPS logistics · Chennai · onsite · Posted 53d ago

    Undisclosed5–7 yrsfulltimeSourced fromLinkedIn

    About a minute. You'll make an account on the way through.

    About this role

    Avant de postuler à un emploi, sélectionnez votre langue de préférence parmi les options disponibles en haut à droite de cette page. Découvrez votre prochaine opportunité au sein d'une organisation qui compte parmi les 500 plus importantes entreprises mondiales. Envisagez des opportunités innovantes, découvrez notre culture enrichissante et travaillez avec des équipes talentueuses qui vous poussent à vous développer chaque jour. Nous savons ce qu’il faut faire pour diriger UPS vers l'avenir : des personnes passionnées dotées d’une combinaison unique de compétences. Si vous avez les qualités, de la motivation, de l'autonomie ou le leadership pour diriger des équipes, il existe des postes adaptés à vos aspirations et à vos compétences d'aujourd'hui et de demain.

    Job Summary Fiche de poste : We are seeking a highly skilled AI Engineer experience in Software Development, Data Science, or Machine Learning to design, develop, and deploy cutting-edge AI systems leveraging Large Language Models (LLMs), Chatbots, Retrieval-Augmented Generation (RAG), and agentic AI architectures. This role involves hands-on development with LLMs, embeddings, RAG pipelines, and multi-agent systems using modern frameworks like LangChain, LangGraph, and LlamaIndex. The ideal candidate has experience with Vertex AI on GCP and IBM WatsonX, fine-tuning, and Agent Development Kits (ADKs), and is excited about building scalable, production-grade AI platforms.

    Responsibilities

    • Agentic AI Development: Design, build, and deploy

    agentic AI systems using frameworks such as LangChain, LangGraph, and related libraries. Develop and deploy

    multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.

    • RAG Pipelines: Implement and optimize

    retrieval-augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for

    grounded, accurate responses .

    • LLM Engineering: Fine-tune and prompt-engineer LLMs for

    task-specific reasoning, planning, and dynamic adaptation . Work with

    LLM/SLM APIs, embeddings, and advanced generative AI techniques .

    • Enterprise AI Platform: Lead the development of enterprise-grade AI platforms integrating

    LLMs, RAG, embeddings, and agentic AI protocols . Implement and standardize

    Model Context Protocol (MCP) for consistent context management across models and agents.

    • MLOps & Observability: Establish and enforce best practices for

    MLOps, monitoring, and observability , ensuring scalable and maintainable AI solutions.

    • Applied AI Prototyping: Rapidly

    prototype, experiment, and iterate to improve AI agent capabilities.

    • Collaboration & Research: Participate in the

    full research cycle : literature review, data exploration, experimentation, and presentation of findings. Collaborate effectively with other engineers, researchers, and data scientists. Contribute to the

    documentation and standardization of technical code and practices.

    Required Education Bachelor’s degree in Computer Science, Engineering, or a related quantitative field.

    Master’s or Ph.D. is a strong plus.

    Required Experience

    • Relevant experience Senior – Min 5+ yrs of relevance experience Intermediate – Min 3+ yrs of relevance experience Associate – Min 2+ yrs of relevant experience
    • 1+ year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.
    • 1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.

    Required Technical Skills

    • Strong programming skills in Python and basics in SQL.
    • Expertise with LLM/SLM APIs, embeddings, and RAG systems.
    • Experience deploying on Google Cloud Platform (GCP) with Vertex AI, and IBM WatsonX.
    • Familiarity with agentic AI protocols and exposure to Agent Development Kits (ADKs).

    Preferred Qualifications

    • Experience implementing Model Context Protocol (MCP) for agent coordination.
    • Prior exposure to Lang Graph, AutoGen, or related orchestration frameworks.
    • Knowledge of MLOps best practices (CI/CD for ML, observability, monitoring, scaling).
    • Familiarity with responsible AI principles (safety, fairness, interpretability).
    • Experience in enterprise-scale deployments of AI-driven platforms.
    • Contributions to open-source AI/ML projects are a plus.

    Type De Contrat en CDI Chez UPS, égalité des chances, traitement équitable et environnement de travail inclusif sont des valeurs clefs auxquelles nous sommes attachés.

    Sourced from linkedin

    Skills

    observabilityRetrieval Augmented GenerationAutoGenFine TuningModel Context ProtocolMLOpsgoogle cloud platformEthical AiEmbeddingsChatbotsLarge Language Models (LLMs)Multi-Agent SystemsGoogle Vertex AIIBM WatsonxPythonAgent Development KitsSQLLanggraphLangchainAgentic AiLlamaindexMCPADKOpenAI SDKArtificial IntelligenceMachine Learning

    About Ups Logistics

    UPS logistics logo

    UPS logistics

    Logistics

    2.8k+

    employees

    1907

    119 years old

    Pune, Maharashtra

    India

    ₹8.3L PA avg

    Avg at Ups Logistics

    About

    UPS Logistics offers innovative transportation and logistics solutions globally, enhancing supply chain efficacy and community support.

    Industries

    LogisticsLogistics / Shipping

    Employee ratings

    10 reviews

    3.5/ 5

    Culture

    2.0

    Career growth

    1.5

    Work-life

    2.0

    Employees rate it well for

    Compensation & Benefits36Job Security35

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    Senior AI Engineer – Python, RAG, Agentic AI, ADK, MCP, GCP, Vertex AI, IBM Watsox · waiting for your command