AI Architect

PwC

. Design and guide production-ready Generative AI solutions for clients from discovery through implementation .

Posted 9/29/2026full-timeRemote • Bulgaria, North Macedonia, Serbia, CroatiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Generative AI solution architecture, including hands-on experience with large language models and cloud-native Azure architecture. Capable of leading technical design, ensuring AI security, and optimizing solution economics while mentoring teams and supporting business development.

Highest-signal resume keywords

Generative AI Solution ArchitectureLarge Language Models (GPT-4, Gemini, Llama)Cloud-Native Azure ArchitectureDevOps and CI/CD PracticesAI Security and Governance

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Generative AI ArchitectureProduction Software SolutionsVector Search and Retrieval EngineeringStructured GenerationRelational and NoSQL Data StoresDockerKubernetesAI Evaluation TechniquesModel EconomicsUser-Centered Product Practices

Soft Skills

LeadershipMentoringCollaborationCommunicationBusiness Development

Tools & Technologies

Azure Machine LearningAzure AI ServicesMicrosoft SQL ServerMongoDBMicrosoft Copilots

Certifications & Qualifications

Microsoft Azure Certification

Industry Keywords

Generative AIAI SecurityResponsible AIModel AdaptationAI Regulation and Assurance Frameworks

Tech Stack

Tools & technologies

AzureCloudDockerKubernetesMicroservicesMongoDBMS SQL ServerNoSQLSQL

About the role

Key responsibilities & impact

Design and guide production-ready Generative AI solutions for clients from discovery through implementation
Lead architecture and delivery of Generative AI solutions
Guide development teams on relevant tools, frameworks, and platforms
Translate business requirements into application, service, and target-state architectures
Own scalability, performance, latency, observability, security, and cost optimisation across AI solutions
Lead technical design and code reviews
Define adaptation approaches including prompting, RAG, fine-tuning, or distillation
Own evaluation strategies including golden datasets, offline and online evaluation, LLM-as-judge, and CI regression testing
Set retrieval quality standards for chunking, hybrid search, reranking, query rewriting, and permission-aware retrieval
Define AI security, privacy, Responsible AI, and governance controls
Own solution economics through model routing, caching, batching, and capacity planning
Support enterprise architecture standards and assess technology solutions
Supervise vendor developers and mentor engineers and junior architects
Support business development by identifying and researching client opportunities
Improve internal design and development practices and maintain documentation
Build internal relationships and strengthen the firm's reputation

Requirements

What you’ll need

5+ years of experience in agile product delivery
Hands-on experience designing and delivering production software solutions at scale
Demonstrated expertise in Generative AI solution architecture
Personally delivered at least one Generative AI system to production and able to explain its architecture, failure modes, operating costs, and lessons learned
Bachelor's or Master's degree in Computer Science or Engineering, or equivalent practical experience
Strong hands-on experience with Generative AI architecture
Experience with large language models such as GPT-4, Gemini, and Llama
Experience with RAG, agent orchestration, and Microsoft Copilots
Experience with vector search and retrieval engineering
Experience with production AI agents
Experience with structured generation
Experience with cloud-native Azure architecture, including Azure Machine Learning and Azure AI services
Experience with service-oriented, event-driven, and microservices architectures
Experience with relational and NoSQL data stores, such as Microsoft SQL Server and MongoDB
Experience with Docker and/or Kubernetes
Experience with DevOps and delivery practices, including CI/CD, automation, and environment management
Working knowledge of user-centred product practices
Experience with AI evaluation using golden datasets, LLM-as-judge, and prompt and model regression testing
Experience with LLMOps and observability
Knowledge of model economics
Knowledge of AI security, including prompt injection, data exfiltration, jailbreak resistance, sandboxing, least-privilege identities, supply-chain risk, and the OWASP Top 10 for LLM Applications
Fluent written and spoken English
Relevant Microsoft Azure certification is preferred
Knowledge of Model Context Protocol, model adaptation, multimodal AI, AI regulation and assurance frameworks, and consulting or professional-services experience are nice to have

Benefits

Comp & perks

Professional, positive, and team-oriented working environment
Professional experience in an international setting
Company training and excellent opportunities for professional and career growth
Challenging and interesting projects
Additional medical insurance
Food vouchers (EUR 102.26 per month)
Sport card
A fringe benefit
Annual bonus
Opportunity to work from home
Central office location in Sofia