We have a Fulltime/Contract position for a AI Engineer – Agentic & RAG Systems with a Consulting Firm.
This will be a 100% Remote opportunity
Interview will happen immediately:
Below is the short summary of the role, please reach out to me on [email protected] with your updated resume:
Looking for someone with 12+ years of experience:
**Job Title: AI Engineer – Agentic & RAG Systems
Location:**
Remote
Department:
AI & Data Platforms
About the Role
As an
AI Engineer
, you will design, build, and operate
agentic AI systems end-to-end
—from concept to production. You’ll work on multi-agent orchestration, Retrieval-Augmented Generation (RAG), evaluation frameworks, and AI guardrails to build safe, reliable, and high-performing systems.
You will collaborate cross-functionally with product, ML, and design teams—bringing ideas to life through strong engineering execution, clear communication, and a low-ego, problem-solving mindset.
RAG Development & Optimization
- Design and implement Retrieval-Augmented Generation pipelines to ground LLMs in enterprise or domain-specific data.
- Make strategic decisions on chunking strategy , embedding models , and retrieval mechanisms to balance context precision, recall, and latency.
- Work with vector databases (Qdrant, Weaviate, pgvector, Pinecone) and embedding frameworks (OpenAI, Hugging Face, Instructor, etc.).
- Diagnose and iterate on challenges like chunk size trade-offs , retrieval quality , context window limits , and grounding accuracy —using structured evaluation and metrics
Minimum Qualifications
- Strong proficiency in Python (FastAPI, Flask, asyncio) and GCP experience is good to have
- Demonstrated hands-on RAG implementation experience with specific tools, models, and evaluation metrics.
- Practical knowledge of agentic frameworks (LangGraph, LangChain) and evaluation ecosystems (LangFuse, LangSmith).
- Excellent communication skills , proven ability to collaborate cross-functionally , and a low-ego, ownership-driven work style.