Senior AI Application Engineer

Job description

THE POSITION: As a Mid-Level AI / Agent Application Engineer, you will be the core builder of the organization's new agentic workforce. Working under the guidance of the Chief AI & Analytics Officer, you will develop the actual agents, write the APIs (tools) the agents will use, and optimize the data pipelines that feed context to the AI. ESSENTIAL DUTIES AND RESPONSIBILITIES: Our employees are tasked with delivering excellent business results through the efforts of their teams. These results are achieved by: Architect, design and implement scalable, multi-agent systems that automate complex, multi-step business processes. Translate existing processes, and develop novel multi-agent architectures for new opportunities Implement agentic solutions leveraging agent orchestration frameworks (e.g., Google ADK, LangGraph, CrewAI, etc.). Design secure "tool-calling" architectures, allowing LLMs to interact with internal databases, CRMs, and APIs safely. Implement LLMOps/AgentOps best practices Mitigate AI-specific security risks, such as prompt injection, hallucination loops, and unauthorized tool execution. Demonstrate a commitment to diversity, equity, and inclusion through continuous development, modeling inclusive behaviors, and proactively managing bias. All other duties as assigned. EXPECTATIONS OF THE JOB: Travel: Some travel may be required for meeting with clients, stakeholders, or off-site personnel/management Hours: 40 hours per week, Monday to Friday The above list reflects the general details necessary to describe the expectations of the position and shall not be construed as the only expectations that may be assigned for the position. An individual in this position must be able to successfully perform the expectations listed above. MINIMUM KNOWLEDGE, SKILLS AND ABILITIES: The requirements listed below are representative of the experience, education, knowledge, skill and/or abilities required. Ph.D. in Computer Science, Engineering (Electrical, Mechanical, Chemical), Mathematics, Physics, Artificial Intelligence, Software Engineering, or a closely related field. 7+ years of software engineering experience, with 3+ years specifically in generative AI, LLMs, or cognitive architectures. Expert-level proficiency in Python and/or TypeScript. Experience with MCP architectures Proficiency in Rust Deep understanding of agentic design patterns (e.g., ReAct, Plan-and-Solve, Reflection, Tree of Thoughts, etc.). Extensive experience with LLM APIs (OpenAI, Anthropic, Google Gemini) and open-weights models (Llama 3, Mistral, etc.). Experience with vector and graph databases Experience with RAG (Retrieval-Augmented Generation) architectures (e.g., GraphRAG, hybrid search). Strong background in cloud architecture (AWS, GCP, or Azure) and containerization (Docker/Kubernetes). PREFERRED QUALIFICATIONS: Experience in enterprise scale deployment of multi-agent architectures. Expert-level proficiency in Rust. Extensive experience with RAG (Retrieval-Augmented Generation) architectures (e.g., GraphRAG, hybrid search).