Jobs and Careers

AI Engineer (Generative AI, LLMs, AIOps)

United States - Remote, United StatesRemotecontractVerifiedPosted 20 Oct 2025

About the role

AI Engineer (Generative AI, LLMs, AIOps)
Kaizen Analytix LLC, an analytics products and services company that gives clients unmatched speed to value through AI/ML solutions and actionable business insights, is seeking qualified candidates for AI Engineer who are highly skilled and experienced professionals responsible for designing, developing, and maintaining complex AI projects and managed data warehouses for hosting large datasets used in the models. The ideal candidate will have a strong understanding of deep learning, vector embeddings, and resolving the challenges of storing the embeddings; and using advanced data engineering principles and best practices, as well as working with massive datasets (100 GB+) that are unstructured, like video, audio images, and text. We seek candidates who can support AI projects with the requisite knowledge on Deep learning, Embeddings, Data engineering skills required for storing Deep learning-based outcomes.

Responsibilities:
Key Responsibilities:

Hands-on Development & Implementation:
- Design, build, fine-tune, and deploy generative models and LLMs for various enterprise applications (e.g., content generation, chatbots, code assistance, data analysis).
- Leverage your deep knowledge of transformer architectures (e.g., GPT, BERT, T5) to fine-tune, optimize, and deploy Large Language Models (LLMs) for specific tasks.
- Implement state-of-the-art techniques such as Agentic AI, Context Engineering - Retrieval-Augmented Generation (RAG), prompt engineering, and model quantization.
- Build, train, and deploy autonomous and semi-autonomous AI agents capable of complex reasoning, tool use, and decision-making.
- Experienced in leveraging state-of-the-art document extraction models for information retrieval using Document Intelligence or Textract cloud services.
- Develop and implement AI/ML models for AIOps use cases, including anomaly detection, predictive monitoring, root cause analysis, and automated remediation.
- Write clean, efficient, well-documented, and production-ready code (primarily Python).
- Build and maintain data pipelines for training, evaluating, and serving AI models.
AI Architecture & Design:
- Design end-to-end architectures for complex AI applications, considering scalability, reliability, security, maintainability, and cost-effectiveness within an enterprise environment.
- Evaluate and select appropriate AI/ML frameworks, models, platforms, and tools for specific projects.
- Collaborate with data scientists, software engineers, DevOps engineers, product managers, and business stakeholders to define requirements and translate them into technical designs.
- Develop and advocate for best practices in AI development, deployment (MLOps), and governance.
Deep Learning & Research:
- Understanding fundamental deep learning concepts (e.g., CNNs, RNNs, LSTMs, Transformers, attention mechanisms) to solve complex problems.
- Stay abreast of the latest advancements and research papers in Gen AI, LLMs, AIOps, and deep learning.
- Experiment with new algorithms, techniques, and tools to drive innovation.
AIOps Integration:
- Integrate AI capabilities into IT operations monitoring, logging, and management tools.
- Analyze operational data (logs, metrics, traces) to identify opportunities for AI-driven improvements.
- Develop systems to automate operational tasks and improve system resilience using AI.

Required Qualifications:

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field. PhD is a plus.
Proven industry experience (typically 3-5+ years, adjust as needed) as an AI/ML Engineer, with hands-on experience building and deploying machine learning models in production.
Demonstra