In a typical day as a Full-Stack AI Engineer, you would...
Lead backend development in Python (Django) and frontend/UI in React.
Develop, deploy, and maintain AI/ML features (ML models, NLP pipelines, AI APIs) for production use.
Integrate AI-driven functionalities into web and cloud-native applications (generative AI, chatbot frameworks, recommender systems).
Experience with modern AI frameworks and libraries such as LangChain, LangGraph, LlamaIndex, Hugging Face Transformers, PyTorch, TensorFlow, and scikit-learn.
Experience integrating AI/LLM APIs such as OpenAI, Azure OpenAI, Anthropic, Google Gemini, Hugging Face, or similar platforms.
Experience building AI-powered applications using vector databases/search technologies such as Pinecone, Qdrant, Milvus, Weaviate, pgvector, Elasticsearch, or OpenSearch.
Design REST APIs and maintain PostgreSQL schemas.
Hands-on experience with AWS, Azure, GCP, and Oracle Cloud, including AWS Marketplace, Azure Marketplace, Google Cloud Marketplace, and Oracle Cloud Marketplace product validation, onboarding, and publishing processes.
Experience automating cloud marketplace publishing and lifecycle management using marketplace APIs, CLI tools, or partner integrations, with exposure to VM images, container-based products, SaaS offerings, BYOL, and usage-based offerings.
Build and automate CI/CD pipelines using Jenkins, Git, and Artifactory for efficient software releases.
Support containerization, orchestration, and application deployment using Docker and Kubernetes.
Collaborate closely with DevOps, cloud, and data engineering teams to drive best practices.
What you need to bring
5+ years of experience in full-stack software development with Python (Django) and React.
2+ years of hands-on experience developing and integrating AI/ML solutions, including Generative AI, NLP, LLMs, or machine learning applications.
Strong grasp of machine learning fundamentals, NLP, and algorithm implementation.
Experience architecting AI-powered features delivered via APIs or microservices.
Practical experience building and automating CI/CD pipelines (Jenkins, Git, Artifactory).
Hands-on exposure to Docker and Kubernetes (deployments, scaling, automation).
Familiarity with DevOps practices and infrastructure automation.
Nice to Have
Certifications in AI/ML, AWS, Azure, or Kubernetes.
Experience deploying large language models or generative AI solutions.
Familiarity with Helm, Terraform, and Infrastructure-as-Code.
Secure AI pipeline delivery, artifact governance, and compliance workflows.
What We Can Offer You
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.
Let's Stay Connected
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
Job
- Engineering
- Job Level:
- TCP_03
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
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