- Company Name
- Dragonfly
- Job Title
- AI Engineer
- Job Description
-
Job title: AI Engineer
Role Summary: Build, own, and scale the intelligence layer of a product‑centric recommender system, combining data science, ML, and systems engineering to leverage LLMs, RAG, agentic AI, and retrieval‑augmented techniques.
Expectations: Deliver production‑grade AI/ML services, iterate rapidly, apply cutting‑edge research pragmatically, maintain high code quality while meeting speed requirements, and collaborate cross‑functionally to translate complex ideas into deployable solutions.
Key Responsibilities
- Own the development and evolution of the recommender engine’s AI layer.
- Design and implement scalable AI/ML pipelines that integrate LLMs, RAG, and agentic architectures.
- Build and maintain data pipelines on BigQuery and PostgreSQL; orchestrate workflows with Docker, Kubernetes, and CI/CD.
- Experiment with search algorithms (BM25, hybrid), ranking metrics (nDCG, Reciprocal Rank), and knowledge graphs.
- Debug and enhance model behavior, reliability, and observability using Langfuse, LangSmith, or OpenTelemetry.
- Translate research insights into production solutions and continuously refine models based on user and stakeholder feedback.
Required Skills
- 3+ years of applied AI experience with recommender systems, retrieval‑augmented generation, or agentic LLM design.
- Proficiency in Python, pandas, NumPy, scikit‑learn, PyTorch, Hugging Face, Vertex AI, and LangChain.
- Deep knowledge of IR techniques: BM25, hybrid search, ranking metrics.
- Experience designing cost‑aware, latency‑optimized agentic LLM systems.
- Comfortable with MLOps practices: Docker, Kubernetes, CI/CD pipelines, GCP or similar cloud environments.
- Familiarity with observability frameworks (Langfuse, LangSmith, OpenTelemetry) and knowledge graph/graph database usage.
- Strong communication, collaborative mindset, and ability to ship quality code quickly.
Required Education & Certifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
- Optional certifications: Google Cloud Professional ML Engineer, AWS Certified Machine Learning – Specialty, or equivalent.