EdSpan

About

EdSpan is an innovative company in the EdTech space, building cutting-edge learning experiences for the next generation of students. Our collaboration with a US-based private school network helps us better understand user needs while expanding our B2C and B2B products to a broader audience. We are currently working on three major projects:

AI tutoring experience — an innovative project that brings real-time interaction with a 3D animated assistant powered by LLM technology. This virtual tutor helps students navigate challenges, provides guidance, and enhances the learning journey in a playful and engaging way.

Tutorpeers – a peer-to-peer tutoring platform with a young teachers marketplace, event booking features and Zoom-like online sessions with additional interactive learning tools.

Spark Incubator – LMS-like system designed to teach kids entrepreneurship.

We have well-defined processes, trying to automate routine things, conduct code reviews, use CI and CD pipelines to validate and ship our code. We use the Agile approach with daily stand-ups, bi-weekly sprints, and other Scrum artifacts. We keep the number of meetings to a minimum so that engineers can focus on writing high-quality code and delivering cool features.

Who you are

We’re hiring our first AI/ML Engineer to lead the development of our AI agents, including prompting, the RAG and evaluation pipelines, potential fine-tuning. So, you’ll play a key role in shaping the technical direction. We’re seeking someone with a strong understanding of machine learning and NLP fundamentals, capable of tackling complex challenges in agentic workflows and optimizing model performance across the stack.

Requirements

• At least 4 years of experience in the field of Machine Learning, working as a Data Engineer, Data Scientist, Machine Learning Engineer, or in a similar role.
• Bachelor’s degree in Computer Science, Mathematics, or equivalent practical experience;
• Proficiency in Python and common data science libraries (pandas, NumPy, scikit-learn);
• In-depth knowledge of machine learning principles, understanding of LLM architectures, prompt optimization, and fine-tuning strategies;
• Skilled in designing and optimizing RAG pipelines, including embedding generation, sparse and dense retrieval, and hybrid search techniques;
• Familiar with LLM evaluation metrics and tools (BLEU, RAGAS, DeepEval, and other);

• Upper-Intermediate level of English (B2) or above.

   

Highly desireable

• Proven experience building AI-driven workflows using frameworks such as LangGraph, AutoGen, or similar orchestration tools;

• Knowledge of AWS cloud and MLOps.

   

Responsibilities

• Design, implement, and optimize LLM prompts to ensure reliable outputs;
• Assist in developing and maintaining AI evaluation workflows, including designing evaluation guidelines and metrics;
• Help design and develop AI data pipelines: collection, storage, annotation, and model improvement;
• Leverage agent orchestration tools to improve and automate AI workflows;
• Collaborate with the product team to ensure AI capabilities power usable product features.

About

EdSpan is an innovative EdTech company dedicated to creating cutting-edge learning experiences that empower the next generation of students. Our collaboration with a US-based private school network helps us better understand user needs while expanding our B2C and B2B products to a broader audience. Our current focus includes an AI-guided tutoring experiences, a peer-to-peer tutoring platform, and a custom learning management system.

We operate within a framework of clearly defined processes supported by automation for routine tasks, and open, productive collaboration across the team. Our workflows are based on Agile principles, with daily stand-ups, bi-weekly sprints, and other key Scrum practices. At the same time, we keep meetings to a minimum to ensure everyone can stay focused on delivering high-quality results and continuing to grow professionally.

Who you are

We’re looking for someone who enjoys working with complex systems — someone who understands how things connect together, handles edge cases, and makes new features fit flawlessly into existing logic.

This role is not like other traditional Business Analyst positions that focus heavily on interaction with stakeholders. On the opposite, this position is about deep, focused work: analyzing changes, mapping flows, and writing clear, complete specifications for engineers — few meetings and lots of thinking. You bring structure, clarity, and a sharp analytical mindset.

Requirements

• At least 4 years in a Business Analyst role and fluency in spoken English;
• Deep theoretical and practical knowledge of BA methodologies and tools — to choose the right approach for each complex case;
• Ability to write concise, clear, and structured user stories in the rule-oriented format;
• Strong interpersonal skills and experience navigating complex stakeholder structures — to align diverse perspectives into one consistent solution;
• Proven skill in documenting and diagramming complex flows (hundreds of elements), in order to make sophisticated systems understandable and maintainable;
• Familiarity with relational databases, to analyze data structures and identify the right points for change;
• Experience working on AI-driven products (AI agents, or AI workflows) is highly desirable — or a strong understanding of agentic systems, prompting, and evals;

• Bachelor’s degree in Computer Science, Information Technology, or a related field — for a strong analytical and technical foundation.

   

Would be a plus

• Familiarity with Mobile platforms and experience delivering applications from concept to successful App Store launch;

• Experience defining and implementing complex API integrations: Payment Service Providers, video streaming platforms, and other.

   

What will you do

• Prepare user stories / change requests based on the collected requirements while working with the Product team and Business stakeholders:
  • analyze the current state (As-Is) as well as impact analysis (To-Be) and identify gaps;
  • prepare or modify existing BMPN diagrams to supplement specifications;
  • thoroughly polish user stories to cover every little detail to minimize product defects;
• Work with the Engineering team during all SDLC stages to clarify the goal, requirements, corner-case scenarios, relevant test cases, etc.
• Proactively work with stakeholders to identify different types of requirements (business, solution, transition requirements, and other);
• Conduct research and analyze the business domain, including competitor analysis, market research, etc.