Job specification
Job title:
Mid AI Full Stack Developer (MEAN/MERN)
Job Overview:
We are looking for a mid-level full-stack developer with strong MEAN/MERN expertise and strong practical experience building and integrating AI solutions, particularly LLM/SLM-based capabilities, into production applications.
Qualifications
- Bachelors degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field is preferred.
- A strong portfolio of completed projects (especially AI/LLM-based solutions) can be considered as an alternative to formal education.
- Minimum 8 years of professional software development experience with a focus on MERN/MEAN stack technologies.
- Hands-on experience designing, integrating, or fine-tuning Large Language Model (LLM) or Small Language Model (SLM) based solutions (either via APIs or open-source models).
- Demonstrated ability to work collaboratively in cross-functional teams.
- Experience providing guidance and support to junior engineers (e.g. pair programming, code reviews, knowledge sharing).
- Effective communication skills, with the ability to clearly explain technical and AI-related concepts to both technical and non-technical stakeholders.
- Capacity to take ownership of features or workstreams and support team leads in planning and execution.
- Good practical knowledge of cloud solutions (AWS preferred); AWS certification is a plus.
- If no certification is present, achieving the AWS Certified Cloud Practitioner within the first months of work will be a requirement for success.
- AI/ML-related certifications (cloud provider or vendor-neutral) are a plus but not mandatory.
Key Responsibilities
- Design, develop, and maintain robust MEAN/MERN applications in line with the organizations strategic direction.
- Build and integrate LLM/SLM-based features into web applications (e.g., AI assistants, smart search, content generation, automation workflows).
- Implement end-to-end AI functionality: from prompt and context design through to API integration, logging, monitoring, and optimization of model behavior.
- Collaborate with engineers, product owners, and other stakeholders to define and deliver high-quality features.
- Contribute to the mentoring and development of junior staff by providing feedback, guidance, and knowledge sharing.
- Uphold high standards of code quality, testing, documentation, and securityboth for core application code and AI integrations.
- Contribute to the establishment and continual improvement of engineering and AI best practices (coding standards, patterns, guidelines).
- Stay informed about technological trends in web development and AI/LLMs and share relevant insights with the team.
- The work is 100% hands-on and implementation-focused.
Skills and Attributes
- Strong analytical and problem-solving skills, including debugging complex, data-driven, or AI-related issues.
- Ability to work both independently and as part of a team, managing priorities in a fast-paced environment.
- Good communication skills, with the ability to break down complex concepts clearly and concisely.
- Ability and willingness to mentor less experienced colleagues.
- Curiosity and dedication to continuous improvement and learning, particularly in the rapidly evolving AI ecosystem.
- Strong sense of ownership, accountability, and attention to detail.
Technical Skills
- Strong proficiency in:
- HTML, CSS, JavaScript, TypeScript
- Node.js, Express.js
- React and/or Angular
- SQL and NoSQL databases (e.g., MongoDB)
- Experience with AI/LLM/SLM-related work, including:
- Integrating LLMs/SLMs via APIs (e.g. OpenAI, Azure/OpenAI, or other hosted LLM providers) or self-hosted/open-source models.
- Building AI-backed features such as chatbots, copilots, summarization, classification, semantic search, or recommendation flows.
- Working with Retrieval-Augmented Generation (RAG) patterns: vector search, embeddings, and injecting context into prompts.
- Basic prompt engineering: designing prompts, system instructions, and guardrails for reliable responses.
- Familiarity with at least some AI/ML ecosystems (e.g. Python-based toolchains, Hugging Face, LangChain, LlamaIndex, etc.) is a strong plus.
- Experience using GitHub (or similar) for version control, pull requests, and code reviews.
- Practical experience with cloud platforms (AWS preferred), including:
- Hosting Node.js/React/Angular services.
- Deploying AI workloads or integrating with managed AI services.
- Good understanding of system design principles, Agile methodologies, and the software development lifecycle (SDLC).
