Key skills

Generative AI (GenAI)Large Language Models (LLMs)PythonC#/.NET/ASP.NETRetrieval-Augmented Generation (RAG)Agentic FrameworksMCP ServersAPI Development and Microservices ArchitectureAzure/AWS Cloud PlatformsDockerKubernetesMLflowAzure DevOpsPrompt EngineeringStakeholder ManagementJavaC#C.NETAIMLNLPGenAIRAGAgenticASP.NETAWSAzureCI/CDCommunication

About this role

Epiq is a values-driven company supporting complex global legal outcomes through modern platforms and AI. The AI Software Engineer will design, develop, and deploy applied AI systems, integrating GenAI, LLMs, agents, and automation into scalable legal operations solutions. The role also involves collaborating across teams, modernizing legacy automations, and promoting secure, efficient software engineering practices.

Responsibilities:

Design, develop, and deploy AI-driven features and intelligent agents for real-world use cases
Integrate GenAI and LLMs into applications via APIs and microservices
Collaborate with product owners, architects, and engineers to transition prototypes into scalable production systems
Drive hyper automation initiatives by modernizing legacy automations using MCP servers and agentic frameworks
Engineer robust, reusable components and services with a focus on performance, scalability, and cost-efficiency
Apply prompt engineering techniques to optimize model interactions and outcomes
Ensure compliance, security, and ethical standards in all AI development
Document processes, architectures, and best practices in Epiq’s internal knowledge base
Integrate external products with Epiq’s proprietary solutions
Stay current with AI advancements and recommend tools, frameworks, and methodologies

Requirements:

3+ years of experience in AI/ML/NLP/LLMs or related fields
Hands-on experience with GenAI, model training, evaluation, and hyperparameter tuning
Experience with MCP servers, agentic frameworks, and Retrieval-Augmented Generation (RAG)
Strong programming skills in Python, C# (.NET/ASP.NET), Java, or similar languages
Familiarity with cloud platforms (Azure/AWS) and their AI services
Experience with API development, microservices architecture, and CI/CD pipelines
Knowledge of tools like Docker, Kubernetes, MLFlow, and Azure DevOps
Solid understanding of software engineering principles, data structures, and algorithms
Excellent communication skills and ability to present technical concepts to non-technical stakeholders
Bachelor's degree in Computer Science or related field (or equivalent experience)
Must be authorized to work in the United States for any employer