Key Responsibilities
- Design, build, and deploy AI-powered applications using Large Language
- Models (LLMs) and modern AI frameworks.
- Develop AI agents, copilots, and workflow automations using platforms such as OpenAI, Azure AI, and LangChain.
- Build Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.
- Develop REST APIs and integrate AI services with enterprise applications and cloud platforms.
- Create reusable prompts, workflows, and AI components to accelerate solution delivery.
- Collaborate with product owners, architects, and developers to translate business requirements into AI solutions.
- Evaluate new AI models, tools, and frameworks, and rapidly prototype innovative use cases.
- Participate in testing, model evaluation, prompt optimization, and performance tuning.
- Document solutions and contribute to reusable assets and best practices.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, or a related field.
- 1–2 years of software development or AI engineering experience.
- Proficiency in Python and familiarity with JavaScript or TypeScript.
- Experience using LLM APIs such as OpenAI or Azure OpenAI.
- Knowledge of prompt engineering and Retrieval-Augmented Generation (RAG).
- Familiarity with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar AI frameworks.
- Understanding of REST APIs, Git, and software development best practices.
- Exposure to cloud platforms such as Azure, AWS, or Google Cloud.
Preferred Skills
- Experience with AI agent frameworks and multi-agent orchestration.
- Familiarity with vector databases such as Pinecone, Azure AI Search, Weaviate, or Chroma.
- Knowledge of FastAPI, Docker, and CI/CD pipelines.
- Exposure to machine learning fundamentals and model evaluation.
- Understanding of enterprise data integration and API development.
What We're Looking For
- Strong curiosity and passion for Generative AI.
- Excellent problem-solving and analytical skills.
- Ability to learn new technologies quickly and build rapid prototypes.
- Strong communication and collaboration skills.
- A builder mindset with a willingness to experiment and innovate.
Nice-to-Have Certifications
- Microsoft Azure AI Engineer Associate
- Microsoft Azure AI Fundamentals (AI-900)
- AWS Certified AI Practitioner
- OpenAI or LangChain certifications (if available)
Architect while working on cutting-edge enterprise AI and Agentic AI solutions.