11 Nov
|
Nameless
|
India
The Role
We are seeking an experienced AI Solutions Architect to partner with engineering, product, and business teams to design and guide the delivery of enterprise-grade, AI-enabled solutions. This is a senior individual contributor role responsible for solution-level architecture across AI initiatives, ensuring designs align with enterprise standards, security requirements, and long-term platform direction.
We will count on you to:
Design and govern AI solution architectures
- Work with business and technology partners to understand problems, opportunities, and constraints.
- Design, document, and communicate solution architectures for AI-enabled systems, from data ingestion through to user-facing applications.
- Ensure architectures align with enterprise standards, reference architectures, and platform strategies.
- Incorporate reuse, standardisation, and security-by-design principles into solution designs.
- Balance agility (“fail fast”) with the resilience required for enterprise production systems.
Support delivery teams
- Partner with Engineering Managers, Tech Leads, and delivery pods to guide architectural decisions throughout delivery.
- Participate in design reviews and provide architectural assurance as part of formal or informal governance processes.
- Support teams during implementation, from infrastructure setup through to production readiness, as needed.
- Enable teams to deliver solutions independently, avoiding over-prescription or unnecessary complexity.
Lead AI innovation and experimentation
- Lead targeted experimentation and technical spikes to evaluate emerging AI technologies, tools, and architectural approaches.
- Design and run proofs of concept to de-risk complex AI solutions before wider adoption.
- Translate experimentation outcomes into clear architectural guidance, patterns, and standards for delivery teams.
- Partner with Engineering Managers, Tech Leads, and the AI CoE to move successful experiments into production-ready solutions.
- Ensure innovation activities consider security, governance, cost, and operability from the outset.
Shape enterprise AI practices
- Contribute to the evolution of enterprise AI architecture patterns, standards, and guidance.
- Influence technology roadmaps by identifying opportunities for platform modernisation and component reuse.
- Participate in architecture communities of practice and knowledge sharing across the organisation.
- Bring a shift-left mindset, ensuring quality, automation, and operability are designed in early.
Cost, risk, and compliance awareness
- Support cost estimation and solution sizing during planning and budget cycles.
- Ensure AI solutions comply with governance, security, privacy, and regulatory requirements.
- Identify architectural risks and trade-offs early and communicate them clearly to stakeholders.
What you need to have:
- 3 - 4 years of relevant professional software engineering experience in production environments;
- 1 - 2 years of hands-on experience working with Large Language Models (LLMs);
- Proficiency in a modern frontend framework, ideally React with TypeScript (Angular is also acceptable);
- Hands-on experience with NestJS/NodeJS;
- Experience with or working knowledge of FastAPI or Django using Python;
- Strong understanding of RESTful APIs;
- Exposure to deploying and maintaining cloud-based systems;
- Strong communication skills in English and Romanian;
- Extensive experience designing and communicating solution architectures for enterprise systems;
- Proven ability to translate requirements into clear architectural designs and decision records;
- Experience evaluating emerging AI tools or platforms and influencing their adoption through evidence-based architectural recommendations;
- Strong experience working with Agile delivery teams and operating in fast-paced, evolving environments;
- Ability to work effectively with both technical and non-technical stakeholders across levels of seniority;
- A self-directed mindset with the ability to operate independently while collaborating across teams.
Technical experience
- Up-to-date application architectures (e.g., microservices, API-driven systems)
- Full-stack or middleware technologies (e.g., JavaScript/TypeScript, .NET, Python)
- Cloud-native architectures and containerisation (e.g., Kubernetes)
- Identity and access management (e.g., OAuth, SAML, MFA)
- Secure DevOps and Secure by Design principles
- Data platforms (e.g., data lakes, analytics, BI tooling)
- Observability and application performance monitoring
- Familiarity with architectural documentation standards (e.g., C4, UML, ArchiMate)
📌 AI Solutions Architect (India)
🏢 Nameless
📍 India