Lead AI Solutions Architect - End-to-End Delivery

Master of Code Global

Mexico

Hybrid

PHP 3,163,000 - 5,272,000

Full time

14 days+

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Benefits offered by this job

Flexible Involvement

Project Choice

Global Clients

AI-Driven Projects

Job summary

Master of Code Global is seeking a Solution Architect to own technical solution definition and provide architectural leadership across its AI professional services portfolio, spanning pre‑sales, discovery, design, estimation, and delivery governance.

You will guide AI pilots and MVPs, support engineering during implementation, validate key technical decisions, resolve blockers, and ensure solutions meet business goals, scope, and non‑functional requirements while mentoring teams and

Qualifications

3+ years in software architecture or senior technical roles.
Hands-on experience validating decisions and prototyping.
Experience in pre-sales or consulting, including architecture, estimation, pricing, and client presentations.
Expertise in modern architectures (microservices, serverless, event-driven), APIs, distributed systems, and major cloud platforms (AWS, Azure, or GCP).
Practical experience with AI/ML technologies, LLM-based systems, cloud AI services, and building AI-enabled products.
Solid understanding of security, privacy, and compliance (e.g., GDPR).

Responsibilities

Lead Discovery & Solution Design: Work with clients to understand business goals, requirements, constraints, and success criteria. Design scalable end-to-end solutions, including architecture, integrations, cloud infrastructure, AI services, security, and scalability.
Drive Estimation & Delivery Planning: Prepare solution estimates, implementation plans, and delivery roadmaps. Identify risks, dependencies, and trade-offs early to support informed decision-making.
Support Pre-sales & Client Engagement: Partner with sales and delivery teams during discovery, solution presentations, and technical discussions, helping clients shape the right approach for their needs.
Enable Successful Delivery: Recommend team structure, support project handover, and stay involved throughout delivery to guide architectural decisions, resolve technical challenges, and support prototypes or PoCs when needed.
Ensure Solution Quality: Review architecture and key implementation decisions, ensuring solutions remain secure, reliable, scalable, maintainable, and cost-efficient.
Manage Change & Technical Risks: Help clients and delivery teams adapt to changing priorities, balancing scope, timelines, and technical constraints while providing clear recommendations.
Document & Share Knowledge: Prepare architecture documentation, communicate key decisions, risks, and dependencies, and mentor engineering teams when needed.
Leverage AI Effectively: Apply AI/ML technologies and AI-assisted development tools to improve discovery, solution design, validation, and delivery while understanding their limitations and risks.