Our IntentWe are seeking a versatile Full-Stack AI Engineer who balances deep AI expertise with the ability to build ground-up software. The ideal candidate has a T-shaped skill profile: highly proficient in at least two of the core areas below, and average/aware across the rest.
- Core Pillars: AI | ML | Frontend | Backend | Databases | Cloud | DevOps | QA
- Key Advantage: Direct experience with Cloud / Azure Foundry or equivalent environments is a strong plus.
To apply for this position, you must have a working project based on the skills mentioned below. Applicants are required to submit screenshots of the running application alongside their resume.Company DescriptionAINE AI is a deep tech company that specializes in developing AI-enabled technology products. Our APIs and customizable hosted products allow legacy and developing software to integrate AI modules readily available in the market.
Key Responsibilities- Architect & Develop: Design and maintain scalable, secure, and high-performance full-stack applications from the ground up.
- AI Integration: Implement and optimize AI/ML modules and APIs into production-ready software workflows.
- Cross-Functional Collaboration: Work closely with data scientists and product managers to translate complex AI requirements into functional, technical specifications.
- Performance Optimization: Ensure the responsiveness of applications and the integrity of data flow between the UI, server, and databases.
- Code Quality: Write clean, maintainable, and well-documented code while participating in rigorous team code reviews.
Required Skills and QualificationsProfessional Experience & Education- Experience: 2+ years of professional, non-internship experience in an AI Engineer, Full Stack Engineer, AI Specialist, AI Analyst, Data Scientist, or Machine Learning Engineer role.
- Education: Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related quantitative/technical field.
- Communication: Strong verbal and written communication skills.
Technical Proficiencies- Programming Languages: Strong proficiency in Java or Python is essential. Experience with C++ or R is beneficial.
- AI/ML Expertise & Frameworks: * Practical understanding of AI/ML concepts and model lifecycles.
- Hands-on experience with AI frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn.
- Experience integrating AI tools and LLM APIs (OpenAI, LangChain, Anthropic) into web workflows.
- Familiarity with vector databases or RAG (Retrieval-Augmented Generation) pipelines is a significant plus.
- Cloud & Infrastructure: Hands-on experience with Cloud platforms (AWS, Azure, or GCP), containerization tools like Docker, and specific AI/ML tools (e.g., S3, EC2, Lambda, and especially Amazon SageMaker).
- Database Management: Solid experience with Relational (PostgreSQL, MySQL) and/or NoSQL (MongoDB, Redis) databases.
Preferred Skills (Strong Plus)
Microsoft & Azure Ecosystem- Hands-on experience with Azure AI Foundry and Azure OpenAI Service.
- Working knowledge of Azure services including Functions, Logic Apps, Power Automate, AI Search, Storage, Key Vault, and Application Insights.
- Experience integrating with Microsoft Dynamics 365, the Power Platform, or Microsoft 365 services.
Methodology & Mindset- Product Mindset: Ability to think deeply about the end-user experience within an AI context.
- Problem-Solving: Strong analytical skills with the ability to work through complex datasets.
- DevOps & Delivery: Understanding of CI/CD pipelines, automated testing, and Agile/Scrum methodologies.
