Solutions Architect at Inspectorio

Ho Chi Minh City, , Spain -

Full Time

Start Date

Immediate

Expiry Date

01 Sep, 26

Salary

0.0

Posted On

03 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Solution Architecture, GenAI Design, Cloud Architecture, Microservices, Event-Driven Architecture, API Design, RAG, LLM Integration, Python, Angular, React, Node.js, PostgreSQL, Google Cloud Platform, Agentic Workflows, Technical Documentation

Industry

Software Development

Description

About the role The Solutions Architect is a senior, hands-on member of Inspectorio's Architecture team. This is an individual-contributor role focused on designing and delivering practical technical solutions to business problems. The Solutions Architect partners closely with the Engineering Leadership Team and Product Management to translate business strategy into well-architected, secure, and cost-effective solutions across all architectural domains: Application (including adherence to Application Security Standards), Data, Integration, Presentation, and Infrastructure. Working within an established architecture team, the Solutions Architect helps define, apply, and continuously improve the architectural patterns, standards, and reference architectures that optimize total cost of ownership and reduce cycle time for delivery through reuse and consistency. They are expected to be deeply current on modern engineering and AI practices - including GenAI solution design, agentic workflows, and AI-assisted software development - and to bring that expertise into Inspectorio's products and engineering process. A successful candidate combines strong technical depth with sound business judgment, communicates clearly across technical and non-technical audiences, and is equally comfortable producing a strategic reference architecture and getting hands-on with a proof of concept. What you'll do Design end-to-end solution architectures for assigned products and initiatives, ensuring alignment with Inspectorio's target architecture, enterprise patterns, and Application Security Standards. Partner with engineering teams and product managers throughout the delivery lifecycle, providing architectural guidance, design reviews, and pragmatic decision support from discovery through production. Contribute to the definition, documentation, and evolution of strategic platforms, architectural patterns, and reference architectures within the architecture community. Apply architecture standards and governance in practice - helping teams adopt patterns, reuse components, and make sound build-vs-buy and technology-selection decisions. Design AI and GenAI solution architectures, including retrieval-augmented generation (RAG), LLM gateway patterns, model selection and evaluation, vector/embedding stores, prompt and context management, and end-to-end observability and cost/token governance. Architect agentic workflows and multi-agent systems - including tool/function calling, Model Context Protocol (MCP) integrations, orchestration, guardrails, human-in-the-loop controls, evaluation harnesses, and tracing. Help define how AI coding assistants and agentic developer tooling (e.g., Claude Code, Cursor, GitHub Copilot, Gemini CLI) are adopted, governed, and integrated into the SDLC to improve developer productivity, quality, and cycle time. Continuously enhance the reliability, performance, scalability, and security of our products and platforms. Produce clear technical documentation, architecture diagrams, and decision records (ADRs) that make designs understandable and actionable for engineering teams and stakeholders. Build proofs of concept and reference implementations to de-risk new technologies and validate architectural approaches before broad adoption. Act as a technical advisor and mentor to engineers and peers on architecture, modern engineering practices, and emerging technology trends. Participate in the evaluation and selection of new software products, platforms, and AI tooling. Qualifications 6+ years of industry-relevant experience, including 4+ years as a solution, technical, or enterprise architect in a complex, ideally global, product or SaaS organization. Demonstrated experience defining, designing, and implementing complex integration and distributed systems, including microservice and event-driven architectures, with an API-first mindset. Proven ability to apply architecture standards and patterns practically to accelerate and enable delivery - balancing strategic intent with pragmatic execution. Hands-on experience designing solutions on a major cloud platform (Google Cloud preferred; AWS or Azure acceptable), along with relevant middleware, messaging (e.g., Kafka/ESB), data, and infrastructure technologies. Familiarity with technologies relevant to our products, including Python, Angular, React, Node.js, PostgreSQL, and Google Cloud. Practical experience architecting AI/GenAI solutions in production or near-production settings - RAG, LLM integration, evaluation, and the operational concerns (cost, latency, observability, safety) that come with them. Working knowledge of agentic AI patterns and frameworks (e.g., agent orchestration, tool use, MCP) and the trade-offs involved in building reliable, observable agentic systems. Hands-on familiarity with AI coding assistants and their role in the modern SDLC, including how to drive adoption, measure impact, and manage associated quality, security, and licensing considerations. Awareness of responsible-AI and data-governance considerations, including handling of sensitive data (e.g., PII), prompt/data leakage risks, and model evaluation. Excellent written and spoken English, with the ability to present ideas and concepts clearly and concisely to both technical and business audiences. Desired qualifications Cloud architecture certification (e.g., Google Professional Cloud Architect, AWS Certified Solutions Architect). Track record of contributing to architecture within a fast-moving product team. Experience in supply chain, quality, compliance, or another regulated B2B domain. Experience with MLOps and ML model lifecycle (training, deployment, active/shadow versioning, monitoring). Familiarity with observability tooling (e.g., OpenTelemetry) and data/analytics stacks (e.g., BigQuery, Looker). Contributions to open-source projects, technical writing, or community involvement. Strong critical-thinking and design-thinking skills, with a collaborative approach to working through ambiguity and competing priorities Benefits Why it would be awesome to work with us 🍹 Unlimited Annual Leave: We prioritize your well-being and trust you to manage your time. 🏝️ Flexible Working: Whether from home, a coffee shop, or our global hubs, work where you're most comfortable. 💪 Project Ownership: You get to lead the initiatives you're passionate about, professionally or socially. 🌱 Grow with us: We're invested in your personal and professional development. 🌎 Global, diverse, and innovative team: Be part of a welcoming community from 30+ countries, where unique perspectives drive innovation. 🤝 Feel at home: Work closely with colleagues who value your voice, share our E.A.C.H. values, and help you be the best version of yourself. 🎉 Celebrate together: Enjoy remote and hub company and team events that strengthen our bonds and build a fun culture. Our Values EXCELLENCE: We pursue mastery and craftsmanship. "Good enough" is our enemy. We have a thirst and desire for knowledge. There's always an opportunity to be better. AUTONOMY: We act independently when recognizing opportunities for improvement. We seek guidance and clear goals instead of orders. We self-assess the quality and impact of our work. COURAGE: We share our opinion, even if it's uncomfortable. We are candid with colleagues. We are willing to experiment and try something new, even if we're not sure it will succeed. HUMBLENESS: We crave opportunities to learn from the people around us. We leave our egos outside the office. We focus on listening to other perspectives.

Responsibilities

Design end-to-end solution architectures for products and initiatives, focusing on scalability, security, and cost-effectiveness. Lead the integration of AI and GenAI capabilities, including agentic workflows and AI-assisted development tools, into the engineering process.