Raluca Bejan

Hi, I’m Raluca. I help startup teams ramp up in GenAI and turn prototypes into production-ready systems. New to GenAI? I'll help you pick viable use cases, avoid traps, and design an approach that fits. Already building? I can help with architecture, evaluation, safety, and monitoring. I bring both hands-on architecture depth and leadership experience. I’ve founded and scaled engineering teams, and I’m happy to coach engineers and managers while we ship. I can help you with: Use-case selection & product shape Identifying what’s viable, what’s risky, and what’s not worth building based on production realities. Agent architecture Designing state/memory systems, tool orchestration, and multi-agent workflows. MCP integration Implementing standardized tool/data access through MCP servers with a focus on reliability patterns. RAG done right Optimizing retrieval, grounding, and SOP execution through evaluation-driven iteration. Quality & evaluation Building infrastructure for golden datasets, automated scoring (LLM-as-judge), and tracing-driven debugging. Safety & governance Implementing guardrails, policy enforcement, and human-in-the-loop approvals for high-risk actions. Team building & execution Navigating hiring, scaling organizations, mentoring leaders, and resolving cross-functional friction. Just book a free call with me and let's chat, you've got nothing to lose.

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  Artificial intelligence

  I’ve built production text-first agent systems that hold up under real constraints—agents vs workflows vs RAG, state/memory, tool calling, and orchestration (single/multi-agent; A2A/LangGraph). I also cover the NLP/LLM fundamentals behind reliability: prompting, grounding, routing, and context management.

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  Building a team

  I’ve scaled engineering teams and led the full people cycle: hiring, performance reviews, growth plans, and leadership coaching. I help founders build the operating cadence and ownership model needed to ship consistently under pressure, while navigating the cross-functional friction that builds up as teams grow.

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  Customer success

  I’ve built evaluation and observability loops that keep agent behavior stable for customers: regression/golden datasets, automated scoring, and tracing-driven debugging. This reduces customer-facing regressions, speeds up incident triage, and creates a continuous improvement loop so releases get better without breaking existing workflows.

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  Product launches

  I’ve shipped production systems and helped teams get from prototype to launch-ready: defining milestones and release gates, reducing delivery risks early, and putting reliable deployment in place: continuous delivery pipelines, environment management, and monitoring, so releases are repeatable, safe, and fast.

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  Product market fit

  I’ve built feasibility and use case frameworks that help teams find and validate the right GenAI product direction: where AI creates real user value, how to define success, and which constraints (cost, latency, risk) shape the solution, so you avoid expensive dead-ends and reach a testable first release fast.

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  Technology and tools

  I’ve built information service integrations that connect agents to real systems, APIs, databases, internal services, and SaaS tools, using clean contracts (i.e. MCP style), permissions, and failure handling, to ensure predictable execution.

• https://www.mdpi.com/2306-5354/11/8/810