AI Solutions Engineer
Summary
Designs, builds, and deploys AI-powered enterprise applications — generative AI, LLMs, chatbots, copilots, AI agents, and RAG architectures with vector databases — bridging business requirements and technical implementation. Core stack: Python/JavaScript/C#/Java, OpenAI/Azure OpenAI, LangChain, cloud APIs, Docker/Kubernetes.
We are looking for an AI Solutions Engineer to design, build, and deploy AI-powered applications and enterprise solutions. The ideal candidate will bridge the gap between business requirements and technical implementation by integrating AI technologies into business workflows and products.
Key Responsibilities:
Design and develop AI-powered applications and automation solutions.
Build and integrate Generative AI, LLMs, chatbots, copilots, and AI agents.
Collaborate with stakeholders to understand business requirements.
Develop APIs and integrations with enterprise applications.
Design Retrieval-Augmented Generation (RAG) architectures and vector database solutions.
Optimize AI performance, reliability, and security.
Deploy solutions using cloud-native technologies and DevOps practices.
Support troubleshooting and continuous improvement of AI solutions.
Required Qualifications:
Bachelor's degree in Computer Science, Engineering, AI, or related field.
3+ years of software engineering or AI development experience.
Proficiency in Python, JavaScript, C#, or Java.
Experience with LLMs, Prompt Engineering, AI Agents, and Generative AI technologies.
Knowledge of Azure OpenAI, OpenAI API, LangChain, Semantic Kernel, or similar frameworks.
Understanding of cloud architecture and API development.
Preferred Qualifications:
Experience with vector databases such as Pinecone, Chroma, or Weaviate.
Familiarity with Docker, Kubernetes, and CI/CD pipelines.
AI and cloud certifications are a plus.