AI Solutions Architect

About Innovecs: Innovecs is a premier global digital transformation technology corporation with a powerful operational footprint expanding across the United States, United Kingdom, European Union, Israel, Australia, and Ukraine. Specializing in high-yield software systems, Innovecs delivers top-tier engineering consulting across Supply Chain, Healthtech, Software & Hightech, and Gaming domains. Recognized for five consecutive years in the Inc. 5000 and the IAOP Global Outsourcing Top 100, Innovecs maintains a Gold-standard reputation in inspiring workspaces and global employer branding.

Position Overview

We are seeking a highly seasoned, technical AI Solutions Architect to lead the design, orchestration, and enterprise-scale implementation of AI-powered systems across our global product and engineering landscape. Moving far beyond isolated experimentation, you will sit at the absolute absolute forefront of the AI evolution—architecting scalable, observable, and strictly governed multi-agent networks. This high-agency leadership track bridges cross-functional business ROI strategies with deep software execution, pioneering context engineering and responsible AI governance lines globally.

Key Responsibilities

• AI Products & System Architecture: Architect, benchmark, and guide the production implementation of AI-driven products, high-throughput APIs, and enterprise platform structures utilizing frontier LLMs and open-source models.
• Agentic AI & Multi-Agent Workflow Orchestration: Design stateful multi-step reasoning systems and multi-agent collaborative workflows using frameworks like LangGraph, CrewAI, and AutoGen, ensuring strict human-in-the-loop checkpoints.
• MCP Ecosystem Engineering: Oversee the deployment and integration of Model Context Protocol (MCP) server ecosystems to seamlessly connect autonomous agents with core enterprise datastores, tool schemas, and legacy application layers.
• AI-Augmented Developer Tooling: Optimize internal engineering productivity by configuring advanced AI-augmented developer environments (e.g., Claude Code, Cursor, GitHub Copilot) into continuous automated testing and deployment pipelines.
• Governance, Compliance & Security: Hardening agent frameworks using security-first principles—enforcing input validation, prompt injection mitigations, OAuth 2.x authentication, and strict compliance alignment with GDPR and the EU AI Act.
• Observability & Telemetry: Build real-time evaluation and observability pipelines to proactively trace, benchmark, and eliminate hallucinations, model drifts, and deployment latency bottlenecks.
• Strategic Roadmap Calibration: Author AI adoption roadmaps, prioritize pipeline business cases based on clear ROI metrics, and present technical architectural layers confidently to executive leadership.

Required Skills & Qualifications

• 5+ years of verified professional experience in AI/ML solution architecture with a demonstrable tracking history of taking complex AI systems from initial prototype to enterprise-scale production.
• Deep engineering expertise handling Large Language Models (LLMs), precision prompt engineering, custom context management, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
• Hands-on production familiarity with stateful agentic orchestration tools, explicitly involving LangChain / LangGraph or multi-agent delegation frameworks (CrewAI, AutoGen).
• Demonstrated experience designing, deploying, and hardening servers using the Model Context Protocol (MCP) for agent-to-tool integration.
• Strong backend programming proficiency in Python, coupled with a solid working familiarity with at least one secondary language (such as Go or TypeScript).
• Experience deploying cloud-native AI infrastructure across AWS, GCP, or Azure, utilizing managed frontier model services (e.g., Amazon Bedrock, Google Vertex AI).
• Solid software engineering fundamentals including modern system design patterns, secure API architectures, automated testing, and CI/CD operations.
• Demonstrated experience leading cross-functional engineering squads on AI-first software delivery tracks.
• Location Context: 100% remote working infrastructure and flexible operational autonomy setup open to qualified professionals operating Worldwide.

Preferred Strategic Indicators (Nice to Have)

• Advanced background in AI security structures, including multi-agent communication standards like Google A2A or IBM BeeAI ACP protocols.
• Familiarity with advanced reasoning/thinking models and their downstream architectural implications on autonomous agent planning cycles.
• Active contributions to open-source AI projects, public MCP server registries, or published technical articles.

What We Offer

• A global executive runway to define and dictate the enterprise AI architecture strategy for a highly celebrated global tech leader.
• Highly competitive, top-tier international compensation package structured around your engineering depth.
• 100% remote-first work flexibility with autonomous outcome-driven environments.
• Comprehensive health, medical insurance, and wellness support programs tailored to your regional hub.
• Dedicated corporate hardware and engineering staging laboratory budgets to configure your home workstation setup.
• A merit-based, transparent corporate culture featuring immense opportunities for continuous learning, engineering progression, and long-term career scaling.