Full Stack Engineer

MISSION OF THE ROLE:

The Full Stack Engineer is part of FinConecta's Technology team, and develops code for our proprietary platform, with remarkable passion for high quality/ attention to detail and problem solving. The role interacts with different areas of the company, and participates in Agile ceremonies. 

RESPONSIBILITIES::

• Develop high quality, maintainable, and scalable solutions
• Design, code review, static analysis, continuous integration
• Participate in the design process and create / edit / review design suggestions and documentation
• Find and implement simple solutions for complex problems
• Interact directly with the product owners and key stakeholders
• Comply with our company's current information security policies
• Report any event or situation that might compromise the company information security

REQUIREMENTS:

• BS or MS degree in Computer Science or a related technical field
• 2+ years of experience as Fullstack Engineer
• Proficient in MERN stack.
• Experience with relational and NoSQL databases (MongoDb preferred)
• Experience with version control systems (ideally Git)
• Java, JAX-RS, JSON, Spring Framework
• OAuth2, RESTful API architecture, OpenAPI Specification,
• Cloud hosting (AWS preferable)
• Excellent analytical skills
• Advanced level of English
• A pragmatic attitude and approach to solving problems
• Willingness to work in a fast-paced environment, learn new technologies, and programming languages
• Excellent communication and interpersonal skills
• A team player with a "let's do it" attitude
• Experience working with Agile/Scrum methodologies.
• Experience working with JIRA software or similar.

DESIRED SKILLS:

• Experience integrating AI/ML APIs (e.g., OpenAI, AWS Bedrock, or similar) into web applications
• Familiarity with prompt engineering and designing workflows for AI-powered agents
• Understanding of LLMs (Large Language Models) and their application in chatbots, search, and document automation
• Knowledge of AI-assisted development tools (e.g., GitHub Copilot, Amazon CodeWhisperer) to enhance productivity
• Experience with data pipelines and basic AI/ML model consumption in production environments
• Understanding of AI ethics, data privacy, and security implications when working with AI models
• Familiarity with vector databases (e.g., Pinecone, Weaviate) and embedding-based search is a plus