Job Summary
We are seeking a highly skilled AI Engineer to design, develop, deploy, and optimize production-grade Artificial Intelligence solutions. The ideal candidate will have advanced expertise in Python AI development, Google Cloud Platform engineering, full-stack AI application development, and CI/CD pipelines, with the ability to take AI solutions from experimentation through production deployment.
Key Responsibilities
- Design, develop, and implement advanced AI/ML solutions using Python and modern AI frameworks.
- Build and integrate AI-powered full-stack applications, including backend services, APIs, and user-facing applications.
- Develop scalable AI services and REST APIs using Python, FastAPI, Flask, or similar frameworks.
- Leverage Google Cloud Platform (Google Cloud Platform) services to build, deploy, and scale AI/ML applications.
- Develop and maintain production-grade CI/CD pipelines for AI and software applications.
- Containerize AI applications using Docker and deploy workloads using Kubernetes/Google Cloud Platform services.
- Integrate AI/ML models, LLMs, APIs, databases, and external data sources into enterprise applications.
- Implement model serving, monitoring, testing, versioning, and continuous improvement practices.
- Collaborate with data scientists, software engineers, cloud engineers, and product teams to deliver end-to-end AI solutions.
- Apply software engineering best practices including unit testing, code reviews, version control, automation, security, and performance optimization.
- Troubleshoot and optimize AI applications for scalability, reliability, latency, and cost.
- Stay current with emerging AI technologies, frameworks, cloud services, and engineering best practices.
Required Skills
- Artificial Intelligence (AI): Mastery
- Python AI: Advanced
- Full Stack Developer – AI: Advanced
- Google Cloud Platform Engineering: Advanced
- CI/CD Pipeline: Advanced
- Strong experience developing production-grade AI/ML applications.
- Strong Python programming and AI/ML framework experience.
- Experience building AI-enabled full-stack applications and APIs.
- Hands-on experience with Google Cloud Platform services and cloud-native architectures.
- Strong understanding of CI/CD, DevOps, Git, automated testing, and deployment pipelines.
- Experience with Docker and Kubernetes is highly preferred.
- Strong understanding of REST APIs, microservices, databases, and distributed systems.
- Excellent problem-solving, communication, and collaboration skills.
Preferred Qualifications
- Experience with Generative AI, LLMs, RAG, prompt engineering, or AI agents.
- Experience with frameworks such as LangChain, LangGraph, LlamaIndex, PyTorch, TensorFlow, or Hugging Face.
- Experience with Google Cloud Platform AI services such as Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub, and Cloud Storage.
- Experience implementing MLOps/LLMOps practices.
- Familiarity with Terraform or other Infrastructure as Code tools.
- Experience with application monitoring, logging, observability, and model performance monitoring.
Education & Experience
- Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related field.
- 5+ years of software/AI engineering experience, with significant hands-on experience delivering AI solutions to production.
- Demonstrated experience owning AI projects from design and development through deployment and production support.
Core Technology Stack
AI/ML: Python, Machine Learning, Generative AI, LLMs, RAG, AI Agents
Cloud: Google Cloud Platform, Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub
Development: Python, FastAPI, Flask, REST APIs, Full Stack Development
DevOps: CI/CD, Git, Docker, Kubernetes, Terraform
AI Frameworks: PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, LlamaIndex
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