Job Description

Job Purpose

The AI Engineer builds production-grade AI systems including RAG pipelines, fine-tuned models, prompt engineering, model evaluation, and scalable pipelines for enterprise deployment.

Key Responsibilities

AI System Development

Build and maintain production AI pipelines and supporting infrastructure. Develop RAG systems, embeddings pipelines, and context-engineering layers. Implement scalable model-serving, orchestration, and automation processes.

Model Engineering & Optimization

Perform model selection, fine-tuning, and optimization for various use cases. Conduct advanced prompt engineering for LLM-based systems. Run model experiments, diagnostics, and performance tuning.

Evaluation & Quality Assurance

Develop evaluation datasets and rigorous testing frameworks. Validate model quality, accuracy, and consistency through experimentation. Ensure models meet production-level reliability and performance standards.

Deployment & Operations

Collaborate with DevOps/MLOps teams to deploy and maintain AI models. Implement monitoring, observability, and error-handling mechanisms. Ensure scalability, operational efficiency, and compliance.

Qualifications & Requirements

Bachelor's degree in Computer Science, AI/ML, Data Science, Software Engineering, or related field. (4-7) years of experience in AI/ML engineering, applied machine learning, or similar roles. Hands-on experience building production AI pipelines. Strong Python skills and familiarity with ML frameworks (TensorFlow, PyTorch, etc.). Knowledge of vector databases, RAG frameworks, and LLM orchestration. Experience with CI/CD, MLOps, cloud environments, and scalable infrastructure. Experience with LLM fine-tuning, evaluation, and advanced prompt engineering. * Experience in enterprise or government-level AI deployments.