Codebridge

We're hiring a Junior Full Stack Developer (React + Node.js) to join our team and work on a booking platform for activities — yachts, diving, and tours. You'll contribute to both the frontend and backend of the product, building features that help users discover and book experiences online, while collaborating closely with developers to deliver high-quality solutions on time. 

Requirements: 

• Knowledge of JavaScript, React, Node.js (Nest), TypeScript, HTML5, CSS3 
• Experience with relational and no-sql databases    
• Knowledge of Rest API 
• Experience in Agile environment (Scrum or Kanban). 
• Self-motivated, dedicated, and willing to go the extra mile; 
• English: working proficiency (async team communication) 

Responsibilities: 

• Enhance and develop existing application 
• Improve visual representation of existing web application 
• Communicate with developers, designers and product owners 
• Ensure timely delivery of solutions according to specification and design

Recruitment Process: 

1. HR Interview 
2. Tech & Final Interviews 
3. Job Offer 

We Offer: 

• Innovation Culture: Work in a team that actively experiments with AI and modern development approaches    
• Flexible Work: Remote work or a modern office in Kyiv   
• Generous Time Off: 20 paid vacation days + 15 sick leave days annually   
• Professional Growth: Compensation for courses, certifications, and learning resources   
• Cutting-Edge Tools: Access to premium AI tools (Cursor Pro, Сlaude Code, GitHub Copilot, etc.)

Codebridge is looking for an Applied AI Engineer to build the AI functionality of a corporate learning platform end to end. Agents — planning, tool use, acting across the product — are the core, surrounded by retrieval, content generation, and labs. Everything is model-agnostic across Claude, OpenAI, and Gemini. 

Responsibilities: 

• Design and ship agents — the core of the role: planning, tool use, memory, and guardrails, orchestrated with LangChain/LangGraph, exposed via MCP where it fits, running behind a provider-abstraction layer with model routing and cost control 
• Build product features end to end — from the front end through backend services to the model call in the cloud 
• Set up and tune retrieval: ingestion, chunking, retrieval quality, reranking, and grounded generation with citations 
• Evolve the content-generation pipeline: grounded generation from ingested sources, structured outputs that survive provider differences, and accuracy checks that keep generated material true to source 
• Develop hands-on lab environments in a sandboxed execution platform: mock APIs, auto-verification harnesses that grade learner work, and managed multi-provider model access with per-user budgets 
• Take charge of evaluation infrastructure: task datasets, deterministic and model-based graders, regression suites, and cross-provider benchmarks 

Requirements: 

• 4+ years in software engineering, with production systems you can walk through end to end 
• 1+ years shipping production LLM applications — agents, tool use, retrieval — with hands-on work across at least two of the three major platforms (Anthropic, OpenAI, Google) 
• Depth in agent development: tool use, memory, multi-step orchestration, and MCP — you've built and debugged MCP servers, not just consumed them 
• Claude Code as a daily working tool, plus working fluency with the OpenAI API and Gemini — or a demonstrated ability to get there fast, since the abstractions matter more than any single SDK 
• Evaluation fluency: task datasets, deterministic and model-based graders, regression suites. "I tested it manually and it looked fine" is an unfinished sentence 
• Solid Python for LLM tooling, with experience in LangChain/LangGraph or an equivalent orchestration framework 
• Comfort with sandboxed cloud execution environments, CI, and API security basics 
• Clear technical communication — you can review someone else's work rigorously and kindly, and explain a model limitation to a non-engineer without jargon 
• A responsible, outcomes-focused mindset 
• Advanced English or higher 

Nice to Have: 

• Experience with TypeScript/Node/React 
• Provider certifications (Anthropic, OpenAI, or Google Cloud AI) or demonstrable equivalent depth 
• Experience with learning platforms, developer education, or technical enablement 
• Experience with LLM gateway/routing layers, structured-output schemas across providers, or multi-model evaluation tooling 
• Public evidence of technical judgment: open-source contributions, technical writing, or talks 

We Offer: 

• Technical Ownership: You own the AI architecture and the standards behind it 
• Modern AI Work: Agents, retrieval and evaluation as the everyday job, not a side experiment 
• Collaborative Environment: A team that values partnership, creativity, and mutual respect 
• Flexible Work: Work remotely from the comfort of your home or join us in our modern Kyiv office 
• Generous Time Off: 20 paid vacation days + 15 sick leave days annually 
• Professional Growth: Compensation for courses, certifications, and learning resources 
• Cutting-Edge Tools: Access to premium AI tools (Cursor Pro, Claude Code, GitHub Copilot, etc.) 

Recruitment Process:    

1. HR&Technical Interview 
2. Client stage 
3. Offer 

We are looking for a Senior Data Engineer / AI Specialist (Agentic AI, AWS) to work on an enterprise AI platform MVP. You will build the data and AI layer: pipelines from multiple enterprise sources, a data lake, agentic AI use cases and predictive models. 

Responsibilities 

• Design and build ETL/ELT pipelines from heterogeneous enterprise sources (ERP, planning, cost and schedule data, documents, external price indices)
• Build and maintain the data lake / lakehouse; ensure data quality, modeling and governance
• Develop agentic AI solutions: multi-agent orchestration, LLM integrations (AWS Bedrock), RAG over unstructured documents such as contracts
• Build classical ML models, for example forecasting cost at completion from historical data
• Evaluate AI output quality and reliability (evals, guardrails)
• Ensure solutions comply with ISO 27001 / SOC 2 data security requirements
• Work closely with the full-stack developer and the client’s product and AI teams

Requirements 

• 5+ years in Data Engineering and/or Applied AI
• Strong Python and SQL
• Practical experience with LLM applications: agents, RAG, prompt engineering, vector search, document processing
• AWS: S3, Bedrock, data services; PostgreSQL
• Experience with classical ML (regression, time-series forecasting)
• Pipeline orchestration and data quality practices
• Fluent English; availability for Central Europe / Middle East hours

Nice to have 

• Databricks (likely platform for ETL and ML on this project), PySpark. Snowflake is also relevant
• MLOps (model deployment, monitoring)
• Experience with AI governance and data readiness

• Domain knowledge of capital projects, cost management or contracts

   

We Offer 

• Innovation Culture: Work in an AI-first team that actively experiments with agentic AI and modern development approaches 
• Meaningful Challenge: Build the data and AI foundation of an enterprise AI platform, from the data lake to production-ready AI agents and predictive models 
• Flexible Work: Remote work or a modern office in Kyiv 
• Generous Time Off: 20 paid vacation days + 15 sick leave days annually 
• Professional Growth: Compensation for courses, certifications (including AWS and Databricks), and learning resources 
• Cutting-Edge Tools: Access to premium AI tools (Cursor Pro, Claude Code, GitHub Copilot, etc.) 

• Supportive Environment: Collaboration, trust, and focus on outcomes rather than micromanagement

   

Recruitment Process 

1. HR Interview 
2. Tech & Final Interviews 
3. Job Offer 

We are looking for a Senior Full-Stack Developer to work on an enterprise AI platform MVP for a global consulting client. You will help turn an existing prototype into a robust, secure and supportable product, working with a client-led product team and following structured engineering processes. 

Responsibilities 

• Develop and harden the web application: frontend (HTML5, CSS), backend (TypeScript, Python) and APIs
• Refactor and stabilize prototype code (including AI-assisted code) to production quality
• Containerize and deploy services on AWS (Docker, ECR, ECS Fargate)
• Work with PostgreSQL and S3, and integrate with LLM services (AWS Bedrock)
• Implement secure engineering practices aligned with ISO 27001 and SOC 2 (access control, logging, secrets management)
• Write automated tests, documentation, and take part in code reviews
• Work with client product owner and the data/AI engineer, following the client’s functional specifications

Requirements 

• 5+ years of commercial full-stack development experience
• Strong TypeScript and Python
• Solid frontend fundamentals (HTML5, CSS, modern JS)
• Hands-on AWS: ECS Fargate, ECR, S3, IAM; Docker
• PostgreSQL and REST API design
• CI/CD, observability and basic IaC
• Experience in security-conscious or regulated environments (ISO 27001 / SOC 2 requirements)
• Experience following formal SDLC and governance processes
• Fluent English; availability to overlap with Central Europe / Middle East working hours

Nice to have 

• Experience with LLM integrations (AWS Bedrock, RAG)
• Experience supporting production systems (break-fix, incident handling)
• Experience in enterprise or consulting-client projects

• Familiarity with BI/dashboards (Power BI)

   

We Offer 

• Innovation Culture: Work in an AI-first team that actively experiments with AI and modern development approaches 
• Meaningful Challenge: Take an enterprise AI platform from prototype to a secure, production-ready product for a global consulting client 
• Flexible Work: Remote work or a modern office in Kyiv 
• Generous Time Off: 20 paid vacation days + 15 sick leave days annually 
• Professional Growth: Compensation for courses, certifications (including AWS), and learning resources 
• Cutting-Edge Tools: Access to premium AI tools (Cursor Pro, Claude Code, GitHub Copilot, etc.) 
• Supportive Environment: Collaboration, trust, and focus on outcomes rather than micromanagement 

Recruitment Process 

1. HR Interview 
2. Tech & Final Interviews 
3. Job Offer