Legal Engineer, Anyone?

We have watched technology disrupt the practice of law many times before. Lawyers have moved from paper files to electronic databases, from fax machines to email, from banker boxes to eDiscovery platforms, from manual review to technology-assisted review, from local servers to cloud platforms, and now from traditional legal technology to generative AI.

Each wave of technology arrived with predictions that everything was about to change overnight. Some things did change dramatically. But the deeper lesson was that technology only creates value when the work around it is redesigned.

Our leadership at Karta Legal has had experience with complex workflows in mega cases like the Madoff bankruptcy and RMBS litigation. And we learned something very valuable through that experience. We required more than excellent lawyering. We required disciplined division of labor, process design, technology adoption, change management, and project management. It required understanding what work needed senior legal judgment, what work could be delegated, what work could be standardized, what work required technology, and what work required quality control.

It was a learning curve but we pivoted and innovated to meet the need. We did it by creating roles that did not exist before. We provided training and upskiled our lawyers. We built newly minted "litigation support" roles. We created entire new departments around "eDiscovery" roles. We taught our lawyers new disciplines, not learned in law school, like project management, agile methodologies, change management, process design, Lean Six Sigma, and tool mastery.

Staffing Question

We see that much of the current legal AI conversation is focused on tools. Should the firm buy Harvey? Should it use CoCounsel? Should it roll out Microsoft Copilot? Should it evaluate Claude, Legora, or other platforms? Should lawyers be allowed to use public AI tools? Should the firm build custom agents? Should AI be used for research, contract review, discovery, drafting, summarization, or knowledge management? We get calls all the time from law firms asking these questions.

Good questions but first we need to answer the foundational questions: Who understands the legal work well enough to know where AI can help? Who understands the technology well enough to know what the tool is actually doing? Who understands the risk well enough to build guardrails? Who understands lawyers well enough to make adoption real? Who understands operations well enough to turn experiments into repeatable workflows? And, indeed, this is the most challenging part of the work ahead.

In complex litigation, success did not come from letting every lawyer do every task. The work was broken into components. Talent was matched to task. People were trained into new responsibilities. Workflows, escalation paths, quality checks, reporting structures, and documentation were created. The effort required distinguishing between work that required legal judgment and work that required execution, organization, technical skill, or process discipline.

The AI era is likewise complex, even if you are in a small firm, and it requires the same discipline.

Job Postings Are Telling Us Something

One of the clearest signs that AI is changing legal staffing is not found in a conference keynote. It is found in Big Law job postings.

The titles are all over the place: AI Legal Engineer, Legal Technology & AI Attorney, Manager of AI & Advisory Solutions, Director of AI & Innovation, AI Governance & Risk Director, AI Solution Manager, AI Enablement Specialist, and AI-focused PMO Project Manager.

The titles differ, but the underlying need is remarkably consistent. Firms are looking for people who can operate between legal practice, technology, knowledge management, data governance, risk, vendors, training, and change management.

Some examples of postings searching for talent are:

1. Legal Engineer. "The role is responsible for designing and operationalizing AI-enabled legal workflows, including prompt design, retrieval pipelines, document templates, evaluations, guardrails, attorney training, adoption metrics, and ongoing workflow maintenance."
2. Manager, AI & Advisory Solutions. "The role focuses on responsible AI adoption in eDiscovery and litigation support, including workflow redesign, defensibility, SOPs, governance, adoption metrics, vendor management, cost forecasting, team development, and attorney training."
3. Legal Technology & AI Attorney. "Lawyer expected to translate emerging technology into practical tools for lawyers and clients, evaluate AI-assisted research and drafting tools, build knowledge infrastructure, lead training, and bring enough substantive credibility to be trusted by practicing lawyers."
4. Director, AI & Innovation. "The role includes responsibility for a multi-year AI roadmap, ROI metrics, responsible AI policy, legal ethics, vendor diligence, practice-group adoption, training by audience, and leadership of a multidisciplinary team."
5. Director, AI Governance & Risk. "JD, 6 to 10 years of practice experience, AI risk and compliance experience, firmwide governance execution, regulatory interpretation, policy development, training, and the ability to advise partners and senior leadership."
6. Legal AI Intern. "The role includes legal workflow analysis, prompt engineering, AI tool and agent development, legal tech research, project management support, testing, quality assurance, documentation, responsible AI use, and data dashboards." That is a lot to ask of an intern!

What stands out in these postings is how broad they are. When firms put all of that into one job description, they are revealing a deeper issue. They know they need a bridge between law and technology. They may not yet know how to staff the bridge.

The Uncomfortable Market Reality

The people who can truly do this work in its broadest sense exist. But there are not many of us

Relatively speaking, only a small number of professionals have practiced law, managed complex legal workflows, implemented technology, redesigned processes, trained lawyers, worked with vendors, understood governance and data risk, and led change in environments where credibility with lawyers is essential.

Firms need to be honest about what they are asking for and understand how to get it.

There are different ways to get there. Firms can compensate and empower a senior hybrid leader who brings those capabilities. That person will be hard to find and will be very expensive. More likely, however, they will have to build a team that divides the work intelligently across legal, technology, knowledge, operations, risk, and training functions.

What does not work is writing a unicorn job description, giving it a modest title, limiting its authority, hiring someone with limited skills or experience, and expecting transformational results.

What is a "Legal Engineer"?

One of our favorite roles out there is that of "legal engineer." We are not sure this means the same to all who use it. It sounds trendy and helpful but it also sounds vague and imprecise.

We suggest that a legal engineer is not merely a lawyer who likes technology. It is also not an IT professional or recent machine learning graduate assigned to support lawyers. At its best, the role describes someone who can translate legal work into systems without stripping away legal judgment.

That person needs to have experience so they can sit with a practice group and map the real workflow, not the idealized version that appears in a policy manual. They can identify where lawyers are repeating work unnecessarily, where templates are inconsistent, where knowledge is trapped in individual inboxes, where review protocols are undocumented, where handoffs fail, and where AI may safely improve speed, quality, or consistency.

A legal engineer can help answer practical questions. Can this contract review workflow be standardized? Can this research task be supported by a vetted prompt template? Can this document set be analyzed with retrieval-augmented generation? Can this knowledge base be structured so AI can use it responsibly? Can this output be evaluated against a human-created benchmark? What human review is required? Who approves the workflow before it is scaled? What should be logged? What should be prohibited? What training is needed? What metrics matter?

That work is essential. It is the difference between underused/under deployed AI and AI as infrastructure.

The Training Debate

Relatedly, one of the biggest concerns about AI is what it means for junior lawyers. If AI can summarize cases, generate first drafts, compare contract provisions, analyze discovery, create chronologies, and prepare outlines, what happens to the traditional training model?

That concern is legitimate. It should lead them to redesign training.

Junior lawyers have always learned by doing. Some of that work was repetitive, but repetition built judgment. Reviewing documents taught lawyers how facts appear in the wild. Drafting first versions taught structure. Preparing chronologies taught case theory. Research taught skepticism. Cite-checking taught precision.

If AI compresses those tasks, firms have to be intentional about replacing the learning value, not just celebrating the time savings.

A junior lawyer still needs to know how to do the work manually before supervising AI-assisted work. They need to know when an answer is incomplete, when a citation is wrong, when a summary misses the central issue, when a clause is off market, when a privilege call requires nuance, and when a draft sounds polished but is strategically weak.

Firms are implementing AI-focused associate development, including programs where first-year associates spend about 20% of billable time learning tools, collaborating on projects, and developing best practices. But it must be emphasized that lawyers still need to understand the underlying work before relying on AI to support it.

Not Just a Big Law Issue

Big Law postings are useful because they make the trend visible. But the issue is not limited to large firms.

Small and midsize firms face the same questions with fewer resources. A global firm may be able to hire a Director of AI Governance, an AI Legal Engineer, an AI Solution Manager, and an AI PMO leader. A small lawyer firm cannot. But that does not mean the work disappears.

Someone still has to decide which tools are approved. Someone has to train lawyers and staff. Someone has to evaluate vendor claims. Someone has to protect confidentiality. Someone has to redesign workflows. Someone has to create policies. Someone has to decide what human review is required. Someone has to measure whether the tool is actually helping.

For smaller firms, the answer may be a trained internal champion, a fractional legal operations advisor, a tech-savvy practice manager, an outside consultant, or a lawyer who is given real time and authority to lead AI adoption.

But it cannot be no one. Buying AI without assigning ownership is how firms end up with expensive shelfware, inconsistent usage, and unmanaged risk.

The Question Law Firm Leaders Should Ask Now

Law firm leaders should be asking who owns AI strategy, who owns governance, who owns training, who owns workflow redesign, who owns adoption metrics, who owns vendor performance, who owns quality control, and who owns the connection between legal judgment and technical execution.

Those questions are not as exciting as a product demo. But they are far more important.

AI will not magically improve a poorly designed workflow. It may only make the dysfunction move faster. The opportunity is to use this moment to do what many firms should have done years ago: map the work, clarify roles, train people deliberately, redesign processes, measure outcomes, and align technology with how legal services are actually delivered.

Legal engineer, anyone? Maybe the title is imperfect. Maybe the market will settle on different language. But the need behind the title is real. Law firms need people who can build the bridge between law and technology, between experimentation and adoption, between innovation theater and measurable value.

That bridge is where the future of legal work is being built.

Karta Legal helps firms staff this work, whether through interim support, fractional leadership, or experienced legal operations and AI professionals who can bridge legal judgment, workflow design, governance, training, and technology adoption. Contact us for information at info@kartalegal.com.