January 5, 2026 
Full-time Job Description…
AI Developer
Job Overview
We are seeking an AI Developer with a strong background in Python, MLOps, Machine Learning (NLP). In this role, you will design and build end-to-end AI solutions—from data ingestion and model training to deployment and monitoring—with a special focus on leveraging large language models (LLMs) and developing agentic AI capabilities.
Key Responsibilities
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Area |
Responsibilities |
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AI/ML Solution Development |
• Design, build, and optimize machine learning models (e.g., classification, regression, NLP, computer vision) using Python frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Develop, fine-tune, and integrate large language models (LLMs) into applications, ensuring they meet performance and scalability requirements.
• Explore and prototype agentic AI solutions that empower autonomous decision-making and intelligent system behaviors.
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On-Premise Platform & Infrastructure |
• Develop and maintain containerized AI/ML workloads on Kubernetes/OpenShift or similar platforms.
• Collaborate with the infrastructure team to optimize hardware resources (GPUs, CPUs, storage) for efficient training and inference.
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MLOps & Workflow Automation |
• Implement streamlined workflows for model training, validation, and deployment while ensuring robust version control and monitoring.
• Maintain and improve existing MLOps practices to support continuous integration and deployment of AI solutions.
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Data Management & Storage |
• Manage on-prem object storage for large datasets, model artifacts, and metadata.
• Implement data versioning and governance strategies to ensure reproducibility and compliance.
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Collaboration & Communication |
• Work closely with data scientists, DevOps engineers, and stakeholders to gather requirements and deliver AI-driven solutions.
• Clearly communicate complex AI/ML concepts, particularly around LLMs and agentic AI, to both technical and non-technical audiences.
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Security & Compliance |
• Adhere to enterprise security policies and compliance standards for on-prem deployments.
• Ensure secure handling of data, credentials, and access controls throughout the ML lifecycle.
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Required Qualifications
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Qualification |
Details |
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Education |
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field. |
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Experience |
5+ years in AI/ML development, data science, or related roles with a proven record of contributing to production-ready AI/ML projects. |
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Technical Skills |
• Proficient in Python, including libraries such as NumPy, Pandas, scikit-learn, TensorFlow, and PyTorch.
• Experience with containerization (Docker) and orchestration (Kubernetes/OpenShift).
• Familiarity with GPU acceleration (e.g., NVIDIA CUDA).
• Exposure to MLOps tools for continuous integration and deployment.
• Strong understanding of data engineering concepts (ETL, data pipelines, data preparation).
• Demonstrated experience working with LLMs and natural language processing frameworks, as well as an interest in agentic AI.
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Soft Skills |
• Excellent problem-solving and analytical skills focused on developing scalable and maintainable solutions.
• Strong communication and collaboration abilities to work effectively with cross-functional teams.
• Capability to articulate complex AI/ML concepts, especially regarding LLMs and autonomous systems, to diverse audiences.
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Preferred Qualifications
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Area |
Details |
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LLM & Agentic AI Expertise |
Experience with fine-tuning and deploying large language models, prompt engineering, or building agent-based AI solutions. |
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Software Engineering |
Strong understanding of software engineering fundamentals (design patterns, data structures, algorithms). |
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Development Practices |
Experience with agile methodologies, code versioning, continuous integration, and continuous deployment practices. |