Note: The job is a remote job and is open to candidates in USA. Epiq is a company that contributes to complex legal outcomes and is seeking a Forward Deployed Legal Engineer to help law firm clients redesign legal work through AI-enabled workflows. The role involves working directly with clients to improve legal processes, create AI solutions, and ensure effective adoption of technology in legal workflows.
Responsibilities
- Work directly with law firm clients and Epiq Advisory teams to understand legal workflows, pain points, handoffs, and goals, then translate them into practical process improvements and AI-enabled solutions
- Identify, prioritize, and document legal AI use cases
- Create, configure, and refine LLM-based workflows, AI agents, prompts, evaluation criteria, and human-in-the-loop review steps tailored to legal work
- Work hands-on with large language models, agent frameworks, retrieval patterns, and legal workflow context to turn concepts into usable prototypes and delivery-ready designs
- Partner with AI Enablement and technical resources to define requirements, data inputs, integrations, permissions, and workflow logic without needing to personally write production code
- Prototype concepts using available AI, automation, and no-code or low-code tools, gather feedback from users, and help convert the strongest ideas into client-ready solutions
- Map current-state and future-state workflows, identify bottlenecks, and recommend process changes that make AI adoption practical, defensible, and measurable
- Coordinate across Data Modernization, Document Management, Knowledge Advisory, and Change Enablement workstreams so AI agents are grounded in trusted content, aligned to system realities, and supported by effective adoption plans
- Partner with lawyers, paralegals, knowledge professionals, and legal operations teams to surface the real problem behind the stated request
- Apply legal training and legal-domain understanding to design workflows that fit how legal work actually gets done
- Establish evaluation criteria and quality benchmarks appropriate to legal contexts, where accuracy, defensibility, and explainability matter
- Define and track adoption, usage, and value-realization metrics tied directly to client outcomes
- Work with the Data Modernization team to align AI agents and workflows with secure data foundations, trusted knowledge sources, confidentiality requirements, and privacy expectations for privileged legal information
- Design solutions that respect client governance, data-residency, retention, and access-control requirements
- Collaborate with Document Management and Knowledge Advisory teams to connect AI use cases to firm content, document repositories, metadata, search, retrieval, and knowledge governance
- Document architecture, data flows, and decisions to support client security review, audit, and risk management
- Capture repeatable patterns from client engagements into reusable workflow maps, agent designs, prompt libraries, playbooks, templates, and enablement materials
- Shape practical approaches within proposals, SOWs, and client presentations in collaboration with AI Enablement, practice leads, and technical delivery teams
- Contribute to business development by demonstrating how legal process improvement and AI agents can create measurable client value
- Stay current on the legal industry, emerging AI capabilities (including agentic workflows), and evolving best practices in legal technology
- Work with Change Enablement colleagues to translate agentic workflows into adoption plans, role-based enablement, and feedback loops that help lawyers and business professionals use new capabilities confidently
Skills
- JD or comparable legal training
- Strong legal-domain fluency
- Hands-on experience creating AI agents and working with large language models in applied legal or professional services settings
- Ability to work directly with lawyers, knowledge professionals, legal operations teams, and technical delivery partners to identify high-value use cases, design agentic workflows, document requirements, test outputs, and guide adoption
- Work directly with law firm clients and Epiq Advisory teams to understand legal workflows, pain points, handoffs, and goals, then translate them into practical process improvements and AI-enabled solutions
- Identify, prioritize, and document legal AI use cases
- Create, configure, and refine LLM-based workflows, AI agents, prompts, evaluation criteria, and human-in-the-loop review steps tailored to legal work
- Work hands-on with large language models, agent frameworks, retrieval patterns, and legal workflow context to turn concepts into usable prototypes and delivery-ready designs
- Prototype concepts using available AI, automation, and no-code or low-code tools, gather feedback from users, and help convert the strongest ideas into client-ready solutions
- Map current-state and future-state workflows, identify bottlenecks, and recommend process changes that make AI adoption practical, defensible, and measurable
- Coordinate across Data Modernization, Document Management, Knowledge Advisory, and Change Enablement workstreams so AI agents are grounded in trusted content, aligned to system realities, and supported by effective adoption plans
- Partner with lawyers, paralegals, knowledge professionals, and legal operations teams to surface the real problem behind the stated request
- Apply legal training and legal-domain understanding to design workflows that fit how legal work actually gets done
- Establish evaluation criteria and quality benchmarks appropriate to legal contexts, where accuracy, defensibility, and explainability matter
- Define and track adoption, usage, and value-realization metrics tied directly to client outcomes
- Work with the Data Modernization team to align AI agents and workflows with secure data foundations, trusted knowledge sources, confidentiality requirements, and privacy expectations for privileged legal information
- Design solutions that respect client governance, data-residency, retention, and access-control requirements
- Collaborate with Document Management and Knowledge Advisory teams to connect AI use cases to firm content, document repositories, metadata, search, retrieval, and knowledge governance
- Document architecture, data flows, and decisions to support client security review, audit, and risk management
- Capture repeatable patterns from client engagements into reusable workflow maps, agent designs, prompt libraries, playbooks, templates, and enablement materials
- Shape practical approaches within proposals, SOWs, and client presentations in collaboration with AI Enablement, practice leads, and technical delivery teams
- Contribute to business development by demonstrating how legal process improvement and AI agents can create measurable client value
- Stay current on the legal industry, emerging AI capabilities (including agentic workflows), and evolving best practices in legal technology
- Work with Change Enablement colleagues to translate agentic workflows into adoption plans, role-based enablement, and feedback loops that help lawyers and business professionals use new capabilities confidently
- Law Degree strongly preferred, with meaningful experience in a law firm, corporate legal department, legal operations, knowledge management, innovation, or legal technology environment
- Ability to collaborate effectively with AI Enablement, Data Modernization, Document Management, Knowledge Advisory, and Change Enablement teams on integrated client solutions
- Experience improving legal or professional services processes through workflow analysis, requirements gathering, process mapping, automation, knowledge management, or operational redesign
- Understanding of law firm culture, legal workflows, and the operational and risk pressures that shape how legal professionals adopt technology (or a strong track record of rapidly building domain expertise in a specialized field)
- A strong grasp of data security, confidentiality, and privacy, and the judgment to apply it in high-stakes, sensitive environments
- Excellent written and verbal communication skills, with the ability to translate between technical and legal audiences
- A practical improvement mindset: comfortable with ambiguity, biased toward action, and energized by helping clients turn new AI capabilities into usable legal workflows
Company Overview