Intermediate AI Engineer – Python, RAG, Agentic AI, ADK, MCP, GCP, Vertex AI, IBM Watsonx

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Job Description:

Job Summary

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

• 5+ years overall experience in software development, data science, or machine learning.
• 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.
• 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).
• Experience implementing Model Context Protocol (MCP) for agent coordination.
• Prior exposure to LangGraph, AutoGen, or related orchestration frameworks.
• Knowledge of MLOps best practices (CI/CD for ML, observability, monitoring, scaling).

Required Technical Skills

Preferred Qualifications

• 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.
• UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

Employee Type:

Permanent