AI Solution Architect (GenAI)

Location: Sofia, Bulgaria; hybrid work arrangements

Company

Avenga is an international engineering firm with 6,000+ experts worldwide, helping businesses operate with AI at the core across industries, technologies, and markets.

What you will do

• Lead technical discovery with clients, identify high-value GenAI use cases, and assess feasibility.
• Design end-to-end GenAI architectures covering model selection, integrations, data flows, and deployment topology.
• Model solution costs through token estimation, model selection, caching strategies, and infrastructure sizing.
• Build and validate prototypes to reduce delivery risk before implementation.
• Support pre-sales with solution proposals, estimates, and technical input for bids.
• Set technical direction for delivery teams and contribute reusable GenAI reference architectures, integration templates, and evaluation frameworks.

Requirements

• 8+ years of experience in software or solution architecture, including 2+ years designing GenAI or LLM-powered solutions.
• Confident client-facing communication, including technical discovery, challenging requirements, and explaining trade-offs to non-technical stakeholders.
• Strong software engineering background with the ability to review production code, assess system design, and guide implementation quality.
• Hands-on prototyping experience with Python or TypeScript.
• Experience with a modern AI coding tool such as Claude Code, Codex, Cursor, or GitHub Copilot, plus the ability to review and correct generated code.
• Experience with RAG architectures, including retrieval strategies, embedding models, vector databases, and reranking.
• Experience with Anthropic or OpenAI LLM APIs, open-weight SLMs/LLMs, and LLM cost management.
• Experience designing agentic solutions with tool use, multi-step workflows, and MCP.
• Experience with at least one cloud AI platform, such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI.
• Fluent English required.

Nice to have

• Experience with agent frameworks such as LangGraph.
• Background in data science or machine learning.
• Experience with multimodal AI.

Culture & Benefits

• Flexible and hybrid work arrangements with laptops and equipment provided.
• Private health insurance and well-being programs.
• Training opportunities and social events.
• Autonomy, trust, support, and a respectful equal-opportunity environment.

Hiring process

• Submit a CV describing core skills and career goals.
• Complete a talent call, technical interview, and, for some roles, a customer interview.