aws
azure
c#
crewai
docker
gcp
github actions
github copilot
java
javascript
jenkins
kubernetes
langchain
.net
python
pytorch
tensorflowRequirements
Must Have:
- Hands-on Experience in either of the following programming languages – Python /C# / Java/ JavaScript.
- AI-centric libraries like TensorFlow, PyTorch, Keras.
- Expertise in generative models such as generative adversarial networks (GANs), variational autoencoders (VAEs).
- Hands-on Experience in using Coding Assistants – GitHub Copilot, Codium, ChatGPT.
- Hands-on Experience in using Agentic AI Platforms – Microsoft Copilot Agents, AutoGPT, CrewAI, Anthropic Claude etc.
- Cloud & MLOps: AWS SageMaker, Azure ML, Google AI Platform.
- Experience with cloud platforms like AWS, Azure, GCP.
- Problem-Solving & Analytical Thinking: Strong problem-solving skills with the ability to quickly identify the root cause of Java application incidents and perform effective troubleshooting.
- Communication Skills: Excellent verbal and written communication skills for interacting with both technical teams and business stakeholders.
- Experience in developing and managing products/solutions using .NET Platform / Java Platform, the Full Stack & Monolith.
- Experience with CI/CD pipelines (e.g., Jenkins, GitLab CI) and DevOps tools (e.g., Docker, Kubernetes) for continuous delivery of Java applications.
- Basic understanding of cloud security best practices.
Generative AI, Copilots, Coding Assistants:
- Hands-on experience with AI coding assistants (e.g., GitHub Copilot) and other AI-driven development tools.
- Design, develop, and maintain IDE extensions for popular development environments such as Visual Studio Code, IntelliJ IDEA, Eclipse, and others.
- In depth understanding of concepts related to prompt engineering, LLM models, context window management, Agentic Systems & workflows.
- Design and develop custom generative models tailored to specific applications.
- Experiment with various neural network architectures such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and more.
- Data cleaning, chunking & populating data into vector stores.
- Experience integrating AI APIs such as OpenAI, Azure OpenAI, LangChain, etc.
- LLM Data stores - Azure Cosmos DB or Azure AI Search.
- Agentic workflows - LangChain, llama, Semantic kernel or AutoGen.
- Azure AI services - specific to GenAI or Agentic Workflow related services such as Azure OpenAI, OpenAI Assistants/AI Agents.
- Proficiency with CI/CD and automation tools: GitHub Actions , Azure DevOps , VS Code.
- Previous involvement in copilot projects for areas like development, customer support.
Prompt Engineering:
- Developing, testing and refining AI-generated text prompts.
- Collaborating with content, product and data teams to align prompts with company goals and user needs.
- Continuously improving prompt quality, performance and the overall AI prompt generation process.
- Experiment with different prompts to optimize AI performance and ensure accuracy and relevance.
- Building a prompt library, Integrating prompts into workflows and applications, Training and tuning AI models.
- Create prompt templates and frameworks for specific use cases.
- Troubleshoot and refine prompts that produce suboptimal results.