AI Engineer - Contract

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.