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About the role

Most teams are racing to ship GenAI features. We’re focused on making them reliable, safe, and production-ready. We need engineers who can break down complex problems and turn powerful models into systems people can actually trust.

Ejento AI, built by Data Science Dojo, is a cutting-edge RAG platform that empowers developers to build retrieval-augmented LLM applications efficiently, safely, and at scale. We’re innovating in AI safety, reliability, and performance by developing robust LLM guardrails and evaluation frameworks, and we’re not here to play small. We need a Software Engineer – Generative AI & LLMs who turns cutting-edge research into robust, real-world solutions. This is more than coding; it’s shaping how Ejento delivers safe, reliable, and high-quality AI outputs that developers can trust, adopt, and scale.

What you will do

  • LLM guardrails & safety frameworks: Design, implement, and maintain safety mechanisms to prevent hallucinations, biases, unsafe outputs, and ensure compliance and ethical AI usage.
  • Evaluation frameworks: Build systems to measure model accuracy, robustness, and real-world performance across use cases.
  • Multi-agent systems: Architect and optimize agentic workflows with tool use, memory, and coordination to turn AI into productive collaborators.
  • Semantic & hybrid search: Optimize RAG, grounding, and reranking systems for precise, context-aware responses.
  • APIs & integrations: Develop scalable APIs and integrations with platforms like Teams, Slack, SharePoint, Notion, and beyond.
  • Experimentation & iteration: Use Ejento to test ideas, identify edge cases, and ship solutions with confidence.
  • Cross-functional collaboration: Partner with product, design, and customer teams to align technical solutions with real-world needs and ensure AI outputs are practical, safe, and effective.

What we are looking for

  • Degree in math, engineering, computer science, or related disciplines. Diverse technical backgrounds welcome.
  • Strong Python programming skills and understanding of OOP, algorithms, and data structures.
  • Experience with LLM inference APIs (OpenAI, Hugging Face, Anthropic, etc.).
  • API development and integration experience for real-world AI applications.
  • Deep interest in LLMs, multi-agent systems, and retrieval-augmented generation (RAG).
  • Familiarity with prompt engineering and leveraging AI tools for coding or automation.
  • Knowledge of frameworks like FastAPI, LangChain, LlamaIndex, and agentic tools like LangGraph or LlamaIndex Agents.
  • Strong problem-solving, communication, and collaboration skills; able to work independently in a fast-moving environment.
  Bonus Points:
  • Large-scale system design and API architecture experience.
  • Docker, serverless architectures, and CI/CD pipeline familiarity.
  • Observability and monitoring tools like Sentry, Langfuse, or Arize.
  • Hands-on experience with LLM guardrails, responsible AI, and safety mechanisms.
  • Experience with agentic frameworks like AutoGen, LangGraph, or similar.
  • Cloud platform experience (AWS, GCP, Azure).
 

At Data Science Dojo, we believe the future belongs to those who can learn, adapt, and apply AI to solve meaningful problems. We look for individuals who stay curious and use AI not just as a tool, but as part of how they think and solve problems, improving the quality, speed, and impact of their work, while ensuring solutions are ethical, responsible, and compliant.

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We would love to hear from you. Submit your application and our team will be in touch.

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