Lenovo
Posted 37 days agoVerified live 1d ago
AI Solution Architect
Brief overview
Remote
UndergradOr in progress
2+ yrsMinimum
190 H-1B approvalsDept. of Labor
28 green cardsCertified filings
AI Solution ArchitecturePythonLLM Prompting and EvaluationRetrieval-Augmented Generation (RAG)Fine-TuningAI GuardrailsDockerKubernetesTerraformREST and GraphQL APIsData Pipelines and ETL/ELT
About the company
Lenovolenovo.com/in/en
Lenovo Group is a computer technology company that manufactures personal computers, smartphones, televisions, and wearable devices.
Visa sponsorship history
4 years sponsoring, last filed FY2026
Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.190H-1B approved
97%approval rate
54new H-1B hires
28PERM certified
$113,547median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
202367
202443
202565
202615
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
202312
202412
20258
202623
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
202321
20247
Top sponsored roles
Advisory IT EngineerSr. Engineer, SWUser Experience (UX) Data AnalystSolution Product ManagerFP&A SPECIALIST
Sponsored employees from
IndiaChinaSwitzerlandBrazilCanada
Job description
Summary
Lenovo is a global technology company focused on delivering AI-enabled devices, infrastructure, software, solutions, and services. The AI Solution Architect designs and validates cost-effective AI architectures, collaborates with development and delivery teams to move solutions from pilot to production, and supports sales and offering teams with technical guidance, prototypes, demos, and proposals.
Responsibilities
- Design end-to-end AI solution architectures — data pipelines, model serving, integration, and security controls — against functional and non-functional requirements
- Define deployment strategy and the path from pilot to production; embed responsible-AI, privacy, and regulatory requirements in the design
- Work day-to-day with the development team through build — design reviews, backlog shaping, and unblocking technical decisions
- Build FDE-style mock-ups, prototypes, and thin vertical slices to de-risk a design or make a concept tangible for the client
- Prove out integration patterns, model behavior, and performance assumptions in code before the team commits to them
- Contribute to the codebase where the situation calls for it — spikes, reference implementations, accelerators — without becoming a permanent delivery resource
- Provide and review technical content for RFP/RFI responses, proposals, and SOWs; support pricing with defensible effort and run-cost inputs
- Design and run demos, proofs of concept, and pilots with explicit success criteria and a defined route to production
- Convert repeatable client patterns into productized offerings, accelerators, and reference architectures
Skills
- • Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience
- • 2–5 years of combined solution architecture and software development experience, including at least one design taken through to delivery
- • Solid understanding of enterprise business applications — ERP, CRM, ITSM, data platforms — and the integration patterns that connect them
- • Practical experience delivering AI/ML or generative-AI solutions into production, with working knowledge of a major cloud platform (AWS, Azure, or Google Cloud)
- • Command of modern AI patterns: RAG, agentic workflows, fine-tuning, evaluation, and guardrails
- • Current hands-on ability to produce a credible prototype independently (Python plus a modern AI/agent framework)
- • Strong communication — able to explain a design to engineers, client stakeholders, and sales; willing to travel to client sites as needed
- • Cloud or AI professional-level certifications (AWS/Azure/GCP architect or ML specialty)
- • Consulting, systems integrator, or ISV background supporting sales and offering teams from a delivery-side role
- • Industry or enterprise functional depth (financial services, healthcare, manufacturing; finance, supply chain, service)
- • MLOps/LLMOps tooling experience, or forward-deployed and embedded engineering work inside a client's environment
Qualifications
Must Haves
- • Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience
- • 2–5 years of combined solution architecture and software development experience, including at least one design taken through to delivery
Nice to Haves
- • Solid understanding of enterprise business applications — ERP, CRM, ITSM, data platforms — and the integration patterns that connect them
- • Practical experience delivering AI/ML or generative-AI solutions into production, with working knowledge of a major cloud platform (AWS, Azure, or Google Cloud)
- • Command of modern AI patterns: RAG, agentic workflows, fine-tuning, evaluation, and guardrails
- • Current hands-on ability to produce a credible prototype independently (Python plus a modern AI/agent framework)
- • Strong communication — able to explain a design to engineers, client stakeholders, and sales; willing to travel to client sites as needed
- • Cloud or AI professional-level certifications (AWS/Azure/GCP architect or ML specialty)
- • Consulting, systems integrator, or ISV background supporting sales and offering teams from a delivery-side role
- • Industry or enterprise functional depth (financial services, healthcare, manufacturing; finance, supply chain, service)
- • MLOps/LLMOps tooling experience, or forward-deployed and embedded engineering work inside a client's environment
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