Senior AI Engineer

🔥 9 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Charger Logistics Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded early 2000's

🚗 Transport

📦 Logistics

Transport • Logistics

Charger Logistics Inc. is a prominent provider of logistics solutions with over 20 years of experience in the industry. The company offers a wide array of services including expedited, dedicated, and temperature-controlled freight transportation. With a commitment to innovation, Charger Logistics integrates advanced IT solutions to enhance their logistics management and provides 24/7 customer service. They maintain a large fleet, including specialized equipment, and over two hundred thousand square feet of warehousing space. Charger Logistics serves both the Canadian and American markets, emphasizing reliability and customer satisfaction in their operations.

📋 Description

• Design, develop, and deploy MCP servers exposing domain services as AI-consumable tools with proper authentication, observability, and error handling • Build multi-agent workflows using orchestration frameworks and agent-to-agent communication protocols for complex logistics automation • Develop and optimize knowledge retrieval pipelines using RAG, KAG, and CAG strategies, selecting the right approach based on query complexity, data volatility, and domain reasoning requirements • Design hybrid retrieval architectures that route between CAG for static reference data, RAG for dynamic operational queries, and KAG for multi-hop reasoning across structured domain knowledge • Implement LLM integration layers including prompt engineering, function calling, structured output parsing, and model routing for domain accuracy • Collaborate with cross-functional teams to collect requirements and translate operational workflows into agent capabilities • Deploy and maintain agent infrastructure on Kubernetes with GitOps practices and observability tooling

🎯 Requirements

• Minimum 3 years of experience with Bachelor's in Computer Science, Artificial Intelligence, or a related technical field • Strong communication skills and experience working in interdisciplinary or team-based environments • Solid understanding of REST APIs, microservices architecture, and AI/ML concepts • Experience building production-grade AI applications in Python—not just notebooks or prototypes • Hands-on proficiency with LLM integration: function calling, tool use, structured outputs (OpenAI, Anthropic, or Google APIs) • Solid understanding of knowledge retrieval patterns including RAG (Retrieval-Augmented Generation), with familiarity of emerging approaches like KAG (Knowledge-Augmented Generation) and CAG (Cache-Augmented Generation) • Proficiency with SQL and at least one analytical data platform (BigQuery, Snowflake, or similar) • Experience with cloud platforms and container orchestration (Kubernetes) • Background in MCP, agent orchestration frameworks, knowledge graphs, or streaming data systems is a strong asset

🏖️ Benefits

• Competitive Salary • Healthcare Benefit Package • Career Growth