AI Engineer

Requirements

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.