
Artificial Intelligence Engineer
2 weeks ago
AI Engineer (Full Stack + DevOps + AI Integration)
Experience Level: 1–2 years
About the RoleWe are looking for a junior AI Engineer with 1–2 years of experience who is eager to grow in the space of AI-assisted development. The ideal candidate should have a Full Stack engineering background with strong DevOps exposure, practical experience with LLM-based applications, and familiarity with automation tools. This role is best suited for someone who has experimented with AI tools like Codex/Clause Code in their development work and wants to build scalable AI-powered applications.
Key Responsibilities- AI-Assisted Development
- Use Clause Code, Codex, or other AI copilots while building applications.
- Implement RAG (Retrieval Augmented Generation) pipelines and work with MCP (Model Context Protocol) for AI integrations.
- Work with APIs of popular LLMs (OpenAI, Anthropic, etc.) to integrate AI features into applications.
- Full Stack Development
- Build and maintain web applications (frontend & backend).
- Work with databases, APIs, and cloud services to deliver end-to-end solutions.
- Contribute to creating responsive and AI-driven user experiences.
- DevOps & Infrastructure
- Support deployment using CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS/GCP/Azure).
- Learn and contribute to infrastructure automation (Terraform, Pulumi).
- Assist in monitoring and scaling applications.
- Automation & Workflow Tools
- Work with n8n, Make.com, Zapier, or similar automation platforms.
- Build simple automation flows to integrate services and reduce manual tasks.
- Collaboration & Learning
- Work closely with senior engineers and product teams to deliver features.
- Document learnings, experiments, and best practices.
- Stay updated with emerging AI tools and frameworks.
- 1–2 years of experience in software development / full stack engineering.
- Basic working knowledge of DevOps practices (CI/CD, Docker, cloud deployments).
- Exposure to LLM-based development and tools such as Codex, Clause Code, or GitHub Copilot.
- Familiarity with RAG pipelines, MCP integrations, and vector databases (Pinecone, FAISS, Weaviate).
- Hands-on experience with at least one automation tool (n8n, Make.com, Zapier).
- Strong problem-solving skills and ability to work independently with AI assistance.
- Exposure to LangChain, LlamaIndex, or other AI orchestration frameworks.
- Experience in deploying AI-powered applications in production.
- Contributions to AI/DevOps-related projects (personal or professional).
- Opportunity to work on real-world AI-first projects with mentorship.
- Hands-on exposure to cutting-edge AI tools and automation workflows.
- A growth-oriented environment with scope to advance into AI Architect / Lead Engineer roles.
- Competitive salary package with performance-based growth.
https://forms.gle/xJvkHkAusJuYtBQi8
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