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.

About ValueMomentum

ValueMomentum is a leading solutions provider for the global property & casualty insurance industry, supported by deep domain and technology capabilities. We offer a comprehensive suite of advisory, development, implementation, and maintenance services across the entire P&C insurance value chain. This includes Underwriting, Claims, Distribution, and more, empowering insurers to stay ahead with sustained growth, high performance, and enhanced stakeholder value. Trusted by over 75 insurers, ValueMomentum is one of the largest standalone insurance-focused solutions providers to the US insurance industry.