Generative & Agentic AI Engineer at Babel Street

Babel Street seeks an engineer to build and operate AI capabilities for intelligence applications. The role focuses on hands-on work implementing generative and agentic AI solutions across investigative and analytical workflows.

Key Responsibilities:

Implement and maintain LLM and SLM pipelines with prompt engineering and inference optimization

Support RAG pipelines, embeddings, and retrieval systems

Build agent-based workflows automating analytical tasks

Write Python code for AI services and integrations

Contribute to evaluation, testing, and hallucination-mitigation techniques

Use AI-assisted development tools (Copilot, Cursor)

Collaborate on integrating AI into user-facing features

Follow AI governance and cost-optimization practices

Required Qualifications:

5+ years software engineering, machine learning, or applied AI experience

Hands-on work with LLMs and/or SLMs, including prompting, inference, or fine-tuning

RAG pipeline experience with embeddings or retrieval systems

Familiarity with agent-based systems or workflow automation

Strong Python proficiency; PyTorch/TensorFlow experience

Machine learning fundamentals understanding

Modern AI/ML tooling experience

Bachelor's degree in CS, Engineering, Data Science, or related field

Preferred: AI applications in intelligence, investigative, or risk domains. Vector databases, graph databases, or knowledge graphs familiarity.