AI Engineering Manager

Role Overview: AARC Group focuses on building multi-agent, agentic AI systems for real, business-critical work. The AI agents designed by the company plan, reason, and act, orchestrating multi-step workflows end to end. The systems automate complex processes across various businesses such as environmental and regulatory compliance, engineering, tax, and financial advisory. Key Responsibilities: - Contribute to the technical and solution architecture for AARC's AI products, including agentic systems, RAG, document intelligence, computer vision, and intelligent automation. - Design autonomous and human-in-the-loop AI agents that plan, reason, and execute multi-step tasks. - Build multi-agent patterns using frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or custom state machines. - Implement tool-use/function-calling for agents to query databases, retrieve documents, call APIs, trigger workflows, and return structured outputs. - Develop computer vision capabilities for imagery and document use cases, including object detection, segmentation, classification, and OCR. - Ship agents and models behind secure APIs, set up agent telemetry, define evaluation suites, and add guardrails and policies suitable for secure environments. - Manage, mentor, and grow the AI engineering team, act as a technical advisor to leadership, and lead knowledge-sharing sessions. Qualifications Required: - Bachelor's or Master's degree in Computer Science, AI/ML, or a related field, or equivalent practical experience. - 8+ years in AI/ML or software engineering, with substantial hands-on experience in building production AI/LLM systems and 4+ years in managing or leading engineers. - Strong programming ability, especially in Python, and familiarity with ML frameworks such as PyTorch or TensorFlow and LLM orchestration frameworks. - Hands-on experience building RAG systems and/or LLM-powered agents in production. - Experience with computer vision and deep-learning frameworks, depth in at least one core area related to AI, and experience with vector databases and document processing at scale. - Experience integrating AI with tools and APIs and owning AI and technical/solution architecture for a product or platform. - People-management experience, clear communication skills, and the ability to present complex AI concepts to non-technical stakeholders. (Note: Any additional details of the company were not provided in the job description.) Role Overview: AARC Group focuses on building multi-agent, agentic AI systems for real, business-critical work. The AI agents designed by the company plan, reason, and act, orchestrating multi-step workflows end to end. The systems automate complex processes across various businesses such as environmental and regulatory compliance, engineering, tax, and financial advisory. Key Responsibilities: - Contribute to the technical and solution architecture for AARC's AI products, including agentic systems, RAG, document intelligence, computer vision, and intelligent automation. - Design autonomous and human-in-the-loop AI agents that plan, reason, and execute multi-step tasks. - Build multi-agent patterns using frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or custom state machines. - Implement tool-use/function-calling for agents to query databases, retrieve documents, call APIs, trigger workflows, and return structured outputs. - Develop computer vision capabilities for imagery and document use cases, including object detection, segmentation, classification, and OCR. - Ship agents and models behind secure APIs, set up agent telemetry, define evaluation suites, and add guardrails and policies suitable for secure environments. - Manage, mentor, and grow the AI engineering team, act as a technical advisor to leadership, and lead knowledge-sharing sessions. Qualifications Required: - Bachelor's or Master's degree in Computer Science, AI/ML, or a related field, or equivalent practical experience. - 8+ years in AI/ML or software engineering, with substantial hands-on experience in building production AI/LLM systems and 4+ years in managing or leading engineers. - Strong programming ability, especially in Python, and familiarity with ML frameworks such as PyTorch or TensorFlow and LLM orchestration frameworks. - Hands-on experience building RAG systems and/or LLM-powered agents in production. - Experience with computer vision and deep-learning frameworks, depth in at least one core area related to AI, and experience with vector databases and document processing at scale. - Experience integrating AI with tools and APIs and owning AI and technical/solution architecture for a product or platform. - People-management experience, clear communication skills, and the ability to present complex AI concepts to non-technical stakeholders. (Note: Any additional details of the company were not provided in the job description.)