Software Engineer (AI Engineer)

At Allegro, we are redefining the e-commerce experience by building an Intelligent Shopping Assistant, a conversational sales channel that understands not just what a user types, but why they are shopping. The Product Intelligence team provides domain-specific grounding for AI solutions, aiming to increase consumer confidence and trust.

• 2-5 years of commercial experience in AI/ML or Software Engineering with a proven track record of developing and deploying robust systems to production.
• Strong proficiency in Python.
• Familiarity with CI/CD pipelines, containerization, and basic observability.
• Familiarity with AI-assisted development tools like Cursor or Copilot.
• Understanding of distributed systems and microservices architecture.
• Experience building and maintaining RESTful APIs in a cloud environment.
• Deep practical understanding of Prompt Engineering, Context Window Management, and interacting with Large Language Models as API endpoints.
• Analytical mindset to debug complex issues in non-deterministic AI systems.
• English proficiency (B2+ level).

Nice to have:

• Hands-on experience developing MCP servers to expose internal data and functionalities to AI agents.
• Experience with LLM orchestration frameworks (ADK) and building multi-turn agents.
• Experience with Google Cloud, specifically Vertex AI features.
• Experience with Kotlin for production-grade services development.
• Experience with Vector Databases or Knowledge Graphs.

Agentic Orchestration:

• Design, implement, and scale stateful, multi-turn workflows using frameworks like Agent Developer Kit, managing complex user intents.

Protocol Integration:

• Build production-grade APIs to expose AI capabilities.
• Implement emerging interoperability standards.
• Secure transactional layers (MCP, A2A, ACP).

Evaluation-Driven Development:

• Systematically measure system performance.
• Optimize core metrics such as User Success Rate and Hallucination Rate.

Context Management:

• Collaborate with Data teams to build and maintain data-serving layers that enrich AI agents with real-time enterprise data.

System Robustness:

• Maintain high code quality through rigorous testing, active code reviews, and full-stack observability using tracing tools like LangFuse.

Continuous Learning:

• Monitor the evolving landscape of Generative AI and Agentic Systems.
• Propose applications of advancements to Allegro's ecosystem.