Senior AI Engineer

Description

CodeValue is looking for a hands-on Senior AI Engineer with real-world experience building and deploying LLM-based and Agentic Systems to production.

You will be responsible for taking AI solutions from concept to reliable, scalable production systems, working across AI, backend, cloud, and infrastructure.

Responsibilities

• Design, develop, and deploy LLM-based and Agentic Systems for production environments.
• Take AI/Agentic solutions from PoC and concept stages to stable, scalable, and reliable production systems.
• Develop backend services and AI solutions using Python.
• Work hands-on with agentic frameworks such as LangGraph, CrewAI, or similar/custom frameworks.
• Deploy and operate AI systems in cloud environments.
• Troubleshoot complex system issues and improve observability, reliability, and performance.
• Collaborate with development, DevOps, security, and other technical teams.

Requirements

• ·      5+ years of hands-on experience in product-based tech companies, with a focus on AI/ML systems.
• ·      Proven track record in designing and implementing GenAI-powered solutions using LLMs and transformer-based architectures.
• ·      Deep understanding of prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning, and LLM-based workflows.
• ·      Strong experience with Azure Cognitive Services.
• ·      Proficiency in Python or other relevant languages (e.g., TypeScript, Go), including use of AI/ML frameworks (e.g., LangChain, Hugging Face, PyTorch).
• ·      Familiarity with containerized environments and orchestration tools (e.g., Docker, Kubernetes).
• ·      Comfortable working with multi-cloud environments (Azure, AWS, or GCP).
• ·      Experience with Agile/Scrum development methodologies.
• ·      Strong communication skills and fluency in English (spoken and written).
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• Preferred Qualifications/ Skills
• ·      Experience with building high-performance distributed systems.
• ·      Familiarity with agentic frameworks for multi-step reasoning or workflow automation.
• ·      Exposure to AI model governance, data compliance, and MLOps pipelines.
• ·      Background in Computer Science or related technical degree.