AI Engineer

• 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-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., Leads software engineering efforts within an agile infrastructure platform team. Develops, reviews, debugs, and governs secure production code using Java full-stack technologies, React, cloud platforms, containers, and relational databases. Drives adoption of AI-assisted engineering tools, establishes validation and security standards, coaches technical teams, promotes SDLC automation, and influences technology decisions. Balances hands-on development with technical leadership and contributes to an inclusive engineering culture. Top Skills: AWSAzureDockerGCPGithub CopilotHibernate/JpaJava 11+KubernetesLarge Language Models (Llms)MySQLOraclePostgresReactRestful ApisSpring BootSpring Framework Airwallex

We are looking for a highly motivated AI Engineer to join our team and contribute to the development of AI-driven solutions for various departments. This role focuses on building production AI agents and MCP (Model Context Protocol) integrations that automate real logistics workflows-dispatch, billing, compliance, and fleet operations-improving the reliability, transparency, and efficiency of AI applications in real-world, high-stakes environments., * 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.

Build and deploy production AI agents and MCP integrations that automate logistics workflows across dispatch, billing, compliance, and fleet operations. Develop multi-agent workflows, hybrid retrieval architectures using RAG, KAG, and CAG, LLM integration layers, and domain-specific AI tools. Collaborate with cross-functional teams to translate operational processes into agent capabilities, while deploying and maintaining infrastructure on Kubernetes using GitOps and observability practices. The summary above was generated by AI

Charger logistics Inc. is a world- class asset-based carrier with locations across North America. With over 20 years of experience providing the best logistics solutions, Charger logistics has transformed into a world-class transport provider and continue to grow., * Competitive Salary

• Healthcare Benefit Package
• Career Growth, 4 Hours Ago In-Office or Remote 171K-269K Annually Senior level 171K-269K Annually Senior level Cloud * Information Technology * Productivity * Security * Software * App development * Automation Develop and productionize machine learning systems for search, retrieval, ranking, recommendations, conversational experiences, and AI agents. Own projects across the ML lifecycle, build evaluation datasets and benchmarks, conduct offline and online evaluations, analyze model quality, and improve system performance. Design scalable architectures addressing reliability, latency, privacy, and cost. Collaborate across product and engineering teams, communicate technical decisions, mentor engineers, and contribute to ML best practices., 5 Days Ago In-Office or Remote 180K-240K Annually Senior level 180K-240K Annually Senior level Artificial Intelligence * Fintech * Payments * Business Intelligence * Financial Services * Generative AI Architect and build high-performance distributed infrastructure for batch and streaming data across global regions. Optimize state management, checkpointing, JVM performance, and exactly-once processing. Develop AI infrastructure including vector indexing, agentic workflows, and real-time data streaming. Own the full software development lifecycle, contribute to shared tooling and SDKs, and mentor engineers through technical leadership and design reviews. Top Skills: Apache FlinkSparkGoJavaJvmKafkaKotlinKubernetesOlap EnginesVector Indexing

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