Applied AI Engineer (Full Stack AI Developer)

We are seeking a motivated Applied AI Engineer with 3–5 years of software engineering experience and hands-on exposure to AI/ML, Generative AI, cloud-native development, and modern software frameworks. The ideal candidate will contribute to the design, development, testing, and deployment of AI-powered solutions while working closely with product and engineering teams.

Main Skills & Experience Required

• 3–5 years of software engineering/development experience.
• Hands-on experience with one or more of:

Python, Java, C#, . NET, Node. js, React, Angular, SQL/NoSQL.

• 1+ year of experience building AI/ML applications.
• Hands-on Generative AI experience with:
• LLM integration — OpenAI, Anthropic, or open-source models
• RAG pipelines
• Prompt Engineering
• Vector Databases
• Exposure to LangChain, LangGraph, PyTorch, and/or TensorFlow.
• 1+ year of cloud-native engineering experience with AWS, Azure, or GCP.
• Exposure to AI cloud services such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.
• Understanding of microservices, FaaS/PaaS, APIs, OOP/OOD, data structures, and algorithms.
• Understanding of software development lifecycle, unit testing, code reviews, CI/CD, and engineering best practices.
• Exposure to Agile, DevSecOps, GitHub, Azure DevOps, SonarQube, MLflow, or similar tools is a plus.
• Exposure to agentic AI frameworks such as LangFuse, LangSmith, or equivalent is preferred.
• Strong communication, collaboration, problem-solving, and willingness to learn.

Key Responsibilities

• Design, develop, test, integrate, and support software and AI-powered solutions.
• Develop scalable and maintainable code using modern programming languages and frameworks.
• Contribute to AI/ML and Generative AI applications, including LLM and RAG solutions.
• Participate in technical design, requirements analysis, code reviews, and testing.
• Use AI tools for code generation, testing, code review, documentation, and development acceleration.
• Build rapid AI-powered prototypes to validate ideas and technical approaches.
• Apply AI-enabled/Agentic SSDLC practices throughout the development lifecycle.
• Collaborate with Product Management, Engineering, Experience, and Delivery teams.
• Support cloud-native applications across AWS, Azure, or GCP.
• Maintain code quality, application reliability, scalability, and security standards.
• Continuously learn and adopt new AI, engineering, and cloud technologies.

Education

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, or related field.

Pay: $55. 00 - $60. 00 per day

Experience:

• prompt engineering: 2 years (Required)
• Generative AI: 2 years (Required)
• LLMs: 2 years (Required)
• LangChain: 1 year (Required)

Work Location: In person