Role Overview
As the AI Engineering Manager for Tmob AI Studio, you will architect and lead the delivery of end-to-end autonomous software solutions for our enterprise clients. Rather than focusing on fine-tuning individual models, your primary challenge will be multi-agent orchestration, seamless enterprise stack integrations, and building robust, unmanned workflows that run 24/7 under strict policy guidelines.
This role demands a unique combination of high-caliber systems engineering, multi-agent systems expertise, team leadership, and a strong consultancy mindset to translate complex business operations into fully automated AI pipelines.
Key Responsibilities
Agent Orchestration & Architecture: Design and manage the high-level orchestration layer of Tmob AI Studio, ensuring diverse AI agents collaborate seamlessly, execute code, and validate outputs against corporate policies.
End-to-End Project Delivery: Analyze client software delivery cycles (specs, design, code, operations) and architect end-to-end, autonomous solutions that compress delivery times from weeks to hours using Tmob AI Studio.
Engineering Leadership & Mentorship: Lead, scale, and mentor an agile team of engineers specializing in agentic workflows, integration layers, and autonomous systems.
Enterprise Integration & Governance: Oversee the integration of the Studio with clients' existing enterprise stacks (Atlassian, DevOps pipelines, Cloud infrastructure) while ensuring bulletproof audit trails, handoffs, and approval gates.
Consultancy & Client Engagement: Serve as the strategic technical voice of Tmob AI Studio, collaborating with executive stakeholders at Fortune 500-level companies to map out their journey toward autonomous software delivery.
Experience: 7+ years of overall experience in Software Engineering, Cloud Architecture, or Systems Engineering, with at least 2+ years in a technical leadership or engineering management role (Lead Engineer, Engineering Manager, etc.).
AI Agent & Orchestration Expertise: Proven hands-on experience or deep technical understanding of Multi-Agent Systems, agentic orchestration frameworks (e.g., LangGraph, CrewAI, AutoGen), and robust LLM API integration.
Ecosystem & Stack Fluency: Deep familiarity with the capabilities of cutting-edge AI tools (Devin, Cursor, Claude, OpenAI, GitHub Copilot) and how they integrate into enterprise environments (Jira, GitHub, Azure DevOps, Docker).
Core Engineering Strength: Exceptional Python skills and mastery of software design patterns, asynchronous processing, event-driven architectures, and secure API management.
Governance & Security Mindset: Understanding of enterprise-grade security, access control, audit trails, and policy-validation mechanisms in software delivery.
Consulting & Delivery Capabilities: Experience in a fast-paced, client-facing software consulting, agency, or enterprise solutions environment. Ability to articulate complex autonomous systems to non-technical business leaders.
Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related quantitative field.