AI Engineer

Role: AI Engineer

Location: Bloomington , IL ( ONSITE )

Mode of Work: Work from Office

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

Experience: 10+ years

Job Description:

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.

Know your team (“Legacy Rewired, Engineering the Future”)

At ValueMomentum’s we are a team of passionate engineers who thrive on tackling complex business challenges with innovative solutions while transforming the P&C insurance value chain. We achieve this through a strong engineering foundation and continuously refining our processes, methodologies, tools, agile delivery teams, and core engineering archetypes. Our core expertise lies in six key areas: Cloud Engineering, Application Engineering, Data Engineering, Core Engineering, Quality Engineering, and Domain expertise.

Join a team that invests in your growth. Our Infinity Program empowers you to build your career with role-specific skill development leveraging immersive learning platforms. You'll have the opportunity to showcase your talents by contributing to impactful projects.

Your 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

Requirements :

Must Have:

• Hands-on Experience in either of the following programming languages – Python /C# / Java/ JavaScript

• AI-centric libraries like TensorFlow, PyTorch, Keras

• Deep proficiency with AI/ML frameworks and libraries including TensorFlow, PyTorch, and Keras, with the ability to architect scalable training and inference pipelines.

• Strong command of Cloud & MLOps platforms, such as AWS SageMaker, Azure Machine Learning, Google AI Platform, including experience building automated model deployment, monitoring, and retraining pipelines.

• 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

• Experience with cloud platforms like AWS, Azure, Google Cloud Platform

• Provide direction, mentorship for junior AI engineers in all projects related aspects

• Participate & perform code reviews of Generative AI, AI Components & Codebase

• Strong problem-solving skills with the ability to quickly identify the root cause of Java application incidents and perform effective troubleshooting.

• 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

• Understanding & working knowledge of Classic ASP, VB6

• 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