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