Toshiba Global Commerce Solutions is seeking a hands-on Senior Enterprise Architect to lead end-to-end solution delivery, combining platform development, client engagement, and partner integrations for major retail platform. This role unifies architecture leadership (design, trade-offs, governance), platform building (infrastructure, core capabilities), client solution delivery (discovery, implementation, support), and AI-enabled acceleration to ensure high-quality, scalable, and future-ready solutions.

You will own the complete architecture lifecycle — from discovery and design to delivery and operational readiness — guiding both the Discovery Track (rapid prototyping, feasibility validation, client alignment) and the Delivery Track (production implementation, measurable outcomes) while building the underlying platform capabilities that enable future solutions. The ideal candidate blends deep architecture expertise, software development, client engagement skills, integration experience, and practical use of AI-assisted development tools to accelerate delivery while maintaining architectural integrity and operational excellence.

Key Focus Areas

Platform Infrastructure & Core Capabilities

• Design and implement scalable platform infrastructure to support emerging use cases and product evolution.
• Build and evolve core platform capabilities — APIs, microservices, data pipelines, and shared services.
• Define architecture patterns and frameworks that enable rapid feature development and platform extensibility.
• Lead technical design for new product capabilities as business requirements evolve.

Client Engagement & Solution Delivery

• Own end-to-end solution delivery for client projects, converting business needs into validated architectures and working implementations.
• Lead client-facing architecture activities: facilitate workshops, present technical solutions, drive approvals, and act as subject-matter expert.
• Translate discovery outcomes into structured delivery backlogs that preserve design intent and architecture standards.
• Ensure traceability from business requirements to implemented solutions with full operational accountability.

Product & Partner Integration Architecture

• Own integration architecture design across partner ecosystems — payments, loyalty, inventory, and cloud services.
• Define and enforce integration patterns, API contracts, and data models ensuring interoperability and scalability.
• Establish and maintain partner integration architectures, including authentication, error handling, and versioning strategies.
• Govern solution design and trade-offs with a focus on performance, security, and operational resilience.

Dual-Track Delivery Leadership

• Lead Discovery and Delivery Tracks within Dual-Track Agile — from exploratory prototypes to validated production implementations.
• Drive Discovery Track activities: rapid prototyping, feasibility validation, and stakeholder alignment before full implementation.
• Translate discovery outcomes into delivery backlogs while maintaining architecture quality and non-functional requirements.
• Ensure seamless transition from discovery to delivery with clear design intent and technical specifications.

AI-Enabled Engineering Acceleration

• Apply AI-assisted tools and workflows (e.g., GitHub Copilot, Cursor, Claude Code) for design, coding, test generation, and documentation.
• Introduce spec-driven and automated validation patterns that improve delivery speed and consistency.
• Coach teams on responsible and practical use of AI to enhance quality and productivity across the software lifecycle.
• Instrument and leverage agentic workflows to accelerate prototyping, code generation, and automated validation.

Hands-On Technical Contribution

• Build production-quality implementations of critical platform components, client solutions, and new infrastructure.
• Lead by example through active coding, prototyping, and technical problem-solving.
• Implement and demo reference code or critical components for both platform capabilities and client solutions.
• Participate in code reviews and hands-on delivery of complex features.
• Work primarily with cloud-native stacks (Java/Spring Boot, TypeScript, React/Vue, Docker/Kubernetes).

Governance, Mentorship & Continuous Improvement

• Define and uphold architecture standards, reusable patterns, and non-functional requirements (security, scalability, observability).
• Mentor engineers and junior architects on design practices, infrastructure patterns, and AI-assisted development.
• Conduct code reviews and enforce architecture governance, promoting best practices across teams.
• Contribute to platform strategy — identifying reusable assets, shared APIs, and infrastructure opportunities.

Key Responsibilities

Architecture & Design

• Lead end-to-end solution architecture across discovery, design, delivery, and operational readiness for both platform and client solutions.
• Design and build new platform infrastructure to support emerging product requirements and use cases.
• Produce and maintain key architectural artifacts: ADRs, interface contracts, data flow diagrams, infrastructure specs, sequencing diagrams, migration/rollback plans, and traceability matrices.
• Define and enforce architecture standards, integration patterns, and non-functional requirements across all solutions.

Platform Development

• Write production code for critical platform features and infrastructure components.
• Build core platform capabilities that enable rapid feature development and solution delivery.
• Establish reusable patterns, shared services, and API-first designs for platform extensibility.

Client Engagement

• Serve as active technical lead in client engagements: facilitate workshops, present solutions, make trade-off decisions.
• Lead Discovery Track activities, rapidly prototyping and validating solutions with stakeholders.
• Drive approvals and alignment across business and technical stakeholders.

Integration & Partnerships

• Establish and maintain partner integration architectures across third-party ecosystems.
• Govern architecture consistency across partner integrations and internal product lines.
• Define authentication strategies (OAuth, SAML, API keys), error handling, and API versioning.

Quality & Governance

• Ensure architecture quality gates and participate in design reviews and release sign-offs.
• Identify and mitigate architecture risks — compatibility, data integrity, scalability, and partner dependencies.
• Own risk analysis and mitigation for architecture decisions, including backward compatibility and compliance constraints.

Continuous Improvement

• Contribute to continuous improvement through reusable patterns, automation, and cross-team alignment.
• Mentor and upskill engineers and architects on AI-assisted development, Dual-Track workflows, and platform best practices.
• Contribute to platform and portfolio strategy, identifying gaps requiring investment and reusable assets.

Qualifications

Must-Have

• Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• 10+ years of professional software development experience, including recent hands-on coding and prototyping in modern technology stacks.
• 5+ years designing cloud-native, microservices, or event-driven architectures (Azure or equivalent cloud platforms).
• Strong experience building platform infrastructure and scalable backend systems.
• Proven experience owning end-to-end solution delivery, including design, implementation, and post-release operational accountability for medium-to-large projects.
• Experience with partner integrations — payments, SaaS APIs, loyalty, inventory, or authentication providers.
• Hands-on experience building prototypes or reference implementations to validate architecture and solution feasibility.
• Expertise in API-first design (REST/OpenAPI).
• Experience with relational/non-relational databases (SQL/NoSQL).
• Solid grasp of containerization, CI/CD, and Kubernetes-based delivery pipelines.
• Practical experience with generative AI and AI-assisted development tools (e.g., GitHub Copilot, Claude Code, Cursor).
• Excellent stakeholder communication skills, able to facilitate workshops, present technical solutions, and collaborate across business and engineering teams.
• Proven leadership in mentoring engineers, conducting code reviews, and enforcing architecture governance.

Preferred

• Strong retail platform domain knowledge (POS systems, store operations, payment processing).
• Certifications such as Azure Solutions Architect, AWS Solutions Architect, or equivalent.
• Experience with API Gateway or Integration Platforms (Azure APIM, Kong, Apigee, MuleSoft, Boomi).
• Solid understanding of API security and compliance (OAuth 2.0/OIDC, JWT, PCI).
• Familiarity with formal specifications (OpenAPI, AsyncAPI, JSON Schema) for contract-driven development.
• Background in distributed systems, microservices architecture, and infrastructure as code.
• Experience leading Dual-Track Agile processes, managing both Discovery and Delivery Tracks, and translating discovery outcomes into actionable backlog items.
• Experience contributing to platform strategy, reusable assets, and API-first designs.

We offer:

• Hired directly by Toshiba and 100% under payroll.
• Benefits of the law (IMSS, INFONAVIT, December day voucher, vacation voucher)
• Life insurance, major medical expenses with dental and visual coverage. (For the employee and direct family members).
• Minor medical expenses insurance.
• Savings fund for employees, capped at the limit of the law.
• Grocery coupons. 
• Pension plan.
• 12 days of vacation plus 6 floating days.

EO: Toshiba Global Commerce Solutions is an equal opportunity/affirmative action employer that evaluates qualified applicants without regard to age, ancestry, color, religious creed, disability, marital status, medical condition, genetic information, military or veteran status, national origin, race, sex, gender, gender identity, gender expression and sexual orientation or any other protected factor. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering