Agentic AI Engineer
Exp: 2-5 Years
23 March 2026
Pittsburgh, USA
Role Overview
We are looking for a highly motivated Agentic AI Engineer with hands-on experience building RAG-based, autonomous AI systems. The ideal candidate has strong Python skills, a solid grasp of modern LLM architectures, and practical experience delivering production-grade Agentic AI, Conversational AI, and Semantic Search solutions with a focus on performance, observability, and cost efficiency.
Key Responsibilities
Design, build, and optimize Agentic AI systems using RAG architectures
Develop data ingestion pipelines including document parsing, OCR, and Computer Vision–based extraction
Implement core RAG building blocks:
Text splitters and chunking strategies
Embedding models (e.g., BGE, OpenAI, sentence transformers)
Vector databases (Weaviate, Pinecone, ChromaDB)
Metadata ingestion, indexing, and metadata-based filtering for retrieval
Retriever strategies, reranking models, and semantic caching
Apply token optimization and context management techniques to improve latency and cost
Integrate and orchestrate LLM APIs (e.g., GPT, Gemini) within multi-agent workflows
Build and deploy Conversational AI / Chatbots and Semantic Search applications
Develop Knowledge Graphs to enhance contextual reasoning and retrieval
Implement observability dashboards using time-series databases to monitor Agentic AI performance, efficiency, and operational cost
Build intuitive UI components using ReactJS or Streamlit
Collaborate with cross-functional teams to move solutions from POC to production
Required Skills
2–5 years of hands-on experience in AI/ML engineering or applied GenAI
Strong proficiency in Python
Experience with OCR / CV pipelines (OpenCV, cloud OCR services, or similar)
Solid understanding of RAG architectures and retrieval optimization
Hands-on experience with vector databases and embedding models
Practical exposure to AI-assisted IDEs such as Claude, Cursor, Windsurf, GitHub Copilot, Codex
Experience building chatbots, conversational AI, or semantic search systems
Working knowledge of Snowflake objects and data integration
Advanced / Nice-to-Have Skills
Model fine-tuning using LoRA / QLoRA
Experience implementing AI guardrails (Profanity filters, guardrails.ai, NeMo Guardrails)
Familiarity with BI dashboards and analytics tools
Experience measuring and optimizing LLM cost, latency, and throughput
Exposure to LangChain, LangGraph, or similar Agentic AI frameworks
What We're Looking For
Strong problem-solving mindset with attention to AI system performance and reliability
Ability to balance innovation with production readiness
Passion for building autonomous, explainable, and scalable AI systems