Senior AI Engineer – Python, RAG, Agentic AI, ADK, MCP, GCP, Vertex AI, IBM Watsox
Indexed description
Job Description
Job Summary
We are seeking a highly skilled AI Engineer with 5+ years of overall 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:
Develop and deploy multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.
- RAG Pipelines:
- LLM Engineering:
Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.
- Enterprise AI Platform:
Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.
- MLOps & Observability:
- Applied AI Prototyping:
- Collaboration & Research:
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).
- 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.
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