AI Fullstack Engineer

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Job Summary

We are seeking a highly skilled and innovative AI Engineer with Full Stack capabilities to join our dynamic team. The ideal candidate will bring a strong blend of expertise in artificial intelligence, modern software engineering practices, and cloud infrastructure. You will be responsible for designing, developing, and deploying intelligent applications that are scalable, resilient, and deliver real business value.

Key Responsibilities

• Develop and deploy end-to-end AI-powered applications leveraging full-stack development best practices.
• Architect and integrate AI/ML models and pipelines using tools like LangChain, Hugging Face, OpenAI, and Anthropic Claude APIs.
• Design and implement microservices, RESTful APIs, and backend systems with scalability and maintainability in mind.
• Leverage cloud platforms (AWS, Azure, GCP) for hosting, automation, and scaling services.
• Integrate CI/CD pipelines to ensure smooth and frequent deployment cycles.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Apply techniques such as content chunking, vector search, embedding models, and retrievers to build advanced AI retrieval systems.
• Ensure robust architecture that can withstand variable load conditions, focusing on fault tolerance and high availability.
• Maintain documentation and adhere to best practices in software development and AI model integration.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of hands-on experience in AI engineering and full-stack development.
• Strong proficiency with AI/ML tools including LangChain, Hugging Face, OpenAI, and Claude APIs.
• Deep understanding of vector databases, retrievers, and modern NLP workflows.
• Proficient in one or more full-stack frameworks (e.g., Node.js, Django, React, Angular).
• Experience with Python
• Experience with cloud platforms (AWS, Azure, GCP) and infrastructure automation tools (e.g., Terraform, CloudFormation).
• Solid experience with CI/CD pipelines, GitOps, and container orchestration (e.g., Docker, Kubernetes).
• Proven ability to architect resilient systems and optimize performance under fluctuating workloads.

Preferred Skills

• Knowledge of prompt engineering and LLM fine-tuning techniques.
• Familiarity with DevSecOps practices and AI compliance requirements.
• Exposure to multimodal models and real-time inference systems.

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