24 hours ago
Sofia, BulgariaSenior
Responsibilities
- Lead the architecture and delivery of production-ready Generative AI solutions for clients.
- Translate business requirements into scalable application, service, and target-state architectures.
- Design reusable RAG, agent orchestration, prompt, evaluation, and model-adaptation patterns.
- Own scalability, performance, latency, observability, security, privacy, governance, and cost optimization.
- Define AI evaluation strategies using golden datasets, offline and online evaluation, LLM-as-judge, and regression testing.
- Set retrieval quality standards for chunking, hybrid search, reranking, query rewriting, and permission-aware retrieval.
- Define controls for prompt injection, data exfiltration, jailbreaks, sandboxing, least-privilege identity, and supply-chain risks.
- Lead technical designs and code reviews and guide delivery against client needs and quality standards.
- Supervise vendor developers and mentor engineers and junior architects.
- Support business development, client opportunity research, internal practice improvements, and technical documentation.
Requirements
- At least 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.
- Personal delivery of at least one Generative AI system to production, including understanding its architecture, failure modes, operating costs, and lessons learned.
- Bachelor's or Master's degree in Computer Science or Engineering, or equivalent practical experience.
- Relevant Microsoft Azure certification, such as Azure Solutions Architect Expert or Azure Developer Associate, is preferred.
- Strong hands-on experience with Generative AI architecture and relevant cloud, software, data engineering, evaluation, operations, and security technologies.
- Experience with LLMs, RAG, agent orchestration, vector search, retrieval engineering, structured generation, cloud-native architecture, containers, orchestration, and DevOps delivery.
- Experience with AI evaluation, LLMOps, observability, model economics, AI security, and governance.
- Knowledge of model adaptation, multimodal AI, Model Context Protocol, AI regulation, and assurance frameworks is preferred.
- Consulting or professional-services experience with external clients is preferred.
- Strong analytical, leadership, troubleshooting, communication, collaboration, client-focus, and continuous-learning skills.
Benefits
- Professional, positive, team-oriented working environment.
- Professional experience in an international setting.
- Company training and opportunities for professional and career growth.
- Challenging and interesting projects.
- Comprehensive employee benefits including additional medical insurance, food vouchers, a sport card, a fringe benefit, and an annual bonus.
- Central office location in Sofia with the opportunity to work from home.
Tech Stack
Categories
Solutions Engineering
About PwC
PwC is a global network of professional services firms providing assurance, tax, and advisory work for businesses and public-sector clients. It sells project-based and managed consulting, audit, and deals services, and implements and integrates business applications. Formed in 1998 by the merger of Price Waterhouse and Coopers & Lybrand, it is headquartered in London and is one of the Big Four accounting firms.