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We are proud to present you with the following opportunity.

About Our Client

Our client is a family-owned legal services business undergoing a major transformation to scale their operations through advanced AI and software solutions. They are building the future of their industry by automating workflows, enhancing efficiency, and creating AI-powered products that redefine how legal services are delivered.

Role Overview

We are seeking a Senior AI Engineer to join the team and lead the development of cutting-edge agentic orchestration systems. This role will focus on two key initiatives:

SaaS Conversion - Transforming the company's existing AI-driven report generation framework into a scalable SaaS product.
Deposition Agent System - Building and orchestrating a new AI agent workflow to automate deposition preparation, integrating diverse data sources and leveraging Model Context Protocol (MCP).

The ideal candidate is an experienced AI engineer with strong integration skills, Python expertise, and hands-on knowledge of agentic orchestration and MCP. You will collaborate directly with the CTO, execute autonomously, and potentially mentor junior engineers as the team expands.

Responsibilities

Design and implement agentic orchestration workflows, including Agent-to-Agent (A2A) communication and self-reinforcement learning.
Lead the SaaS conversion of the company's existing AI-based product, ensuring scalability, security, and reliability.
Build the Deposition Agent System, integrating APIs and data pipelines (email, CRM, file systems) into LLM-powered agents.
Work with Model Context Protocol (MCP) to connect and contextualize data across multiple systems.
Evaluate and integrate AI frameworks (e.g., N8N, CrewAI, or alternatives) to optimize agent performance.
Collaborate with the CTO and stakeholders to translate business needs into technical solutions.
Provide technical guidance and mentorship as the AI team grows

Requirements

5+ years of software engineering experience, with at least 3 years in AI/ML or agent-based systems.
Proven experience with agentic orchestration, Model Context Protocol (MCP), and Agent-to-Agent (A2A) Protocols (hands-on preferred, theoretical knowledge acceptable).
Strong coding skills in Python, with the ability to leverage "vibe coding" tools (e.g., Claude, Copilot) for rapid development.
Experience with API integrations, data pipelines, and connecting multi-system environments.
Understanding of SaaS product architecture and deployment.
Ability to work autonomously while following high-level direction from the CTO.
Excellent problem-solving skills and adaptability to emerging AI technologies

Benefits