Artificial Intelligence Engineer

About the Role Are you passionate about building state-of-the-art agentic systems, context architectures, and scalable AI infrastructure? We are seeking a Senior AI Systems Engineer & Architect to serve as a technical authority across our AI engineering initiatives. In this role, you will bridge the gap between high-level architectural vision and hands-on engineering execution. You’ll lead the design and implementation of production-grade multi-agent frameworks, advanced context and memory systems, and enterprise LLMOps pipelines—setting the technical standards that empower engineering teams to build reliable, high-performance AI solutions at scale. What You’ll Do - Design Next-Gen Agentic Architectures: Architect and deploy production-ready multi-agent workflows, establishing robust patterns for agent loops, tool execution, state management, retry strategies, and fail-safe recovery. - Advance Context & Knowledge Systems: Build scalable retrieval, memory, and knowledge graph architectures (including GraphRAG, LPG, and RDF) to optimize LLM reasoning and contextual awareness. - Drive Interoperability & Integration: Establish standardized, reusable AI capabilities, skills, and plugins utilizing cutting-edge protocols such as MCP, A2A, and custom tool-calling frameworks. - Elevate AI Reliability & LLMOps: Set up comprehensive evaluation frameworks, test harnesses, observability platforms, and production debugging standards across the entire AI lifecycle. - Optimize System Performance: Lead strategies around token economics, inference efficiency, dynamic model routing, latency reduction, and cost optimization. - Shape AI Engineering Standards: Partner cross-functionally with Product, Architecture, and Domain Experts to define technology roadmaps and drive best practices across AI-assisted SDLC and modern AI UX patterns (such as AG-UI and human-in-the-loop workflows). What We’re Looking For - Deep AI Engineering Expertise: Proven track record of architecting and deploying agentic systems, multi-agent orchestrations, and advanced RAG/retrieval frameworks in production. - Core Software Engineering Rigor: Strong foundation in distributed systems, spec-driven development, Test-Driven Development (TDD), Domain-Driven Design (DDD), and modern API design. - Ecosystem Mastery: Deep familiarity with modern AI protocols and tools (e.g., Model Context Protocol (MCP), Agent-to-Agent (A2A), agentic coding tools, and evaluation frameworks). - Multimodal Capabilities: Experience or strong interest in multimodal AI execution spanning text, voice, and vision systems. - Technical Leadership: Natural ability to mentor engineering teams, influence technical direction, and establish reusable architectural patterns across complex environments. Why Join Us? - Cutting-Edge Tech Stack: Work directly on leading-edge agentic AI, context engineering, and multimodal systems at the forefront of the industry. - High-Impact Leadership: Own key technical decisions and set the benchmark for enterprise AI engineering standard methodologies. - Collaborative Environment: Join a forward-thinking culture that values software engineering excellence, innovation, and continuous learning.