Job Description:

Epiq is seeking a highly skilled Lead AI Software Engineer to join our Operations Engineering team. This role is ideal for candidates who are passionate about building applied AI systems-not just writing code, but designing intelligent solutions that drive automation, efficiency, and innovation across legal operations.

You'll work at the intersection of software engineering and AI, leveraging modern technologies such as GenAI, LLMs, MCP servers, and agentic frameworks to build scalable, production-ready solutions. This role will also champion modern development practices and utilize Azure DevOps for agile delivery and ticketing.

Key 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.

Qualifications & Experience

• 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).

#LI-KS1 #LI-Remote

The Compensation range for this role is 120,000 to 170,000 USD annually and may be eligible for an annual bonus.

Your specific salary will be determined based on several factors:

• Location-based market rate for the role
• Your abilities in relation to the job specification
• Performance during screening and interview
• Pay parity with the wider team in the considered location

Further details about the package will be provided during the initial screening call with the Talent Acquisition Team.

Click here to learn about Epiq's Benefits.

Epiq Leadership Compass

Fosters Relationships & Collaboration

Builds trust and alignment through open communication, shared goals, and strong partnerships to drive collective success.

• Build trust-based partnerships
• Nurture long-term relationships
• Remove collaboration barriers
• Celebrate cross-team success

Engages & Influences

Inspires action and alignment through clear communication, purposeful influence, and a compelling vision.

• Use storytelling to build buy-in
• Align communication with organizational goals
• Guild alignment through strong engagement

Maximizes Performance

Sets and reinforces performance standards that drive results, ensure accountability, and align with Epiq's goals.

• Use data to identify improvement opportunities
• Make informed decisions
• Align team goals with boarder strategy
• Empower teams to manage their own goals
• Translate vision into clear priorities
• Prepare for disruptions with strong change management

Achieves Operational Success

Drives continuous improvement and operational excellence through smart processes, data insights, and quality execution.

• Improve workflows for team efficiency
• Use clear documentation and expectations
• Resolve issues quickly using data and feedback