AI Engineer

AI Engineer

Location: Hybrid (New York, NY) Duration: Long-term

Primary skills: AI, ML, Generative AI, GitHub CoPilot, Prompt Engineering

About the Job

We are looking for an experienced AI Engineer with a strong background in Artificial Intelligence, Machine Learning, Generative AI, Coding Assistants, AI Assistants, and Agile Software Development. The successful candidate will be responsible for every stage of AI, Generative AI development, from conceptualization and design to rigorous testing and successful deployment.

Key Responsibilities AI & ML:

• Develop, implement machine learning models and algorithms to solve complex business problems and enhance AI-driven applications.
• Collaborate with cross-functional teams, including data scientists, software engineers, to integrate AI solutions into existing products and services.
• Hands-on expertise in Python programming and familiarity with AI and machine learning frameworks.
• Conduct data analysis, preprocessing, and feature engineering to extract valuable insights using Generative AI, LLMs.
• Stay updated on the latest AI, ML, Generative AI advancements, research papers, tools, incorporating them into AI development projects.
• Optimize Generative AI models for performance, scalability, and efficiency, leveraging cloud-based resources and distributed computing frameworks.
• Actively participate in code reviews and collaborative problem-solving sessions, contributing to the improvement of AI solutions and development processes.
• Troubleshoot and resolve AI-related issues, ensuring the reliability and accuracy of AI-driven applications.

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.

Required Skills & Qualifications:

• 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.

Optional Skills & Qualifications:

• Experience in developing, managing products/solutions using .NET Platform / Java Platform either 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.