Dechert LLP is seeking an AI Engineer to join the Dechert Innovation Lab, working alongside teams across the firm to explore, validate, and prototype emerging AI-enabled technologies. This role focuses on building proof-of-concept and pilot solutions that can improve legal services and day-to-day firm operations, with pathways to transition successful work into enterprise applications.
Working onsite in Washington, DC, you will help frame innovation opportunities, run technical discovery, and develop experimental applications across generative AI, retrieval-augmented generation (RAG), workflow automation, and intelligent agents. You will also evaluate outcomes and recommend next steps based on business impact, complexity, governance needs, and time-to-value.
Responsibilities
- Partner with attorneys and cross-functional teams across practice groups, legal project management, knowledge management, finance, risk, client development, and business services to identify innovation opportunities and understand workflows, pain points, and desired outcomes.
- Lead technical discovery and innovation sessions to assess business problems for AI, automation, and emerging technologies.
- Rapidly design, develop, and evaluate proof-of-concept and pilot solutions using approved and emerging AI platforms, APIs, low-code tools, workflow automation platforms, and custom development technologies.
- Build and test experimental AI-enabled applications, including generative AI assistants, document and knowledge-search solutions, RAG applications, workflow copilots, intelligent agents, and decision-support tools.
- Select technical approaches based on innovation potential, business value, solution complexity, data sensitivity, scalability, supportability, and time-to-value.
- Measure solution success using feasibility, time saved, adoption potential, accuracy, user satisfaction, process-cycle reduction, risk reduction, and business impact.
- Evaluate pilot outcomes and recommend whether to transition successful experiments to the appropriate enterprise application teams.
- Stay current on AI engineering practices and legal-industry AI use cases, including emerging tools and platforms, AI governance requirements, and relevant technology trends, and propose new technologies for future evaluation.
- Participate in intake prioritization, solution estimation, innovation pipeline planning, vendor evaluations, and portfolio reporting.
- Perform other responsibilities as needed.
Requirements
- Experience with Generative AI and related tooling and concepts, including Model Context Protocol (MCP), Azure/OpenAI, Large Language Model (LLM) workflows, Claude, Microsoft CoPilot, prompt engineering, retrieval-augmented generation, embeddings, vector databases, AI agents, model evaluation, and responsible AI practices.
- Application development concepts including APIs, microservices, web applications, databases, authentication, authorization, logging, monitoring, testing, and CI/CD practices.
- Experience with automation and orchestration technologies, including workflow platforms, robotic process automation, low-code/no-code development tools, and integration platforms.
- Familiarity with software development methodologies such as Agile, Kanban, rapid prototyping, product discovery, and iterative delivery.
- Strong software engineering skills in one or more modern programming languages, including Python, JavaScript/TypeScript, C#, ASP.NET Core, SQL, or similar.
- Ability to build and deploy AI-enabled applications using APIs, SDKs, orchestration frameworks, cloud services, and enterprise platforms.
- Ability to translate ambiguous business needs into testable hypotheses and experiment designs.
- Strong consultative and communication skills across attorneys, business leaders, technical teams, vendors, and nontechnical users.
- Strong analytical, problem-solving, and systems-thinking abilities.
- Ability to balance speed and experimentation with security, quality, governance, maintainability, and long-term supportability.
- Experience designing user-centered solutions and incorporating feedback into rapid experiment cycles.
- Comfort with ambiguity and multiple concurrent initiatives in a fast-moving environment.
- Resilience in iterative experimentation, including learning from unsuccessful outcomes and adapting approaches across testing cycles.
- Genuine curiosity about applying AI to legal, client-service, and business-operations challenges.
- Interest in working directly with end users to test solutions.
- Interest in responsible AI, data protection, human-centered design, and practical technology governance.
- Enthusiasm for hands-on experimentation and continuous learning, including evaluating emerging technologies.
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science, Artificial Intelligence, or related technical discipline (or an equivalent combination of education, training, and relevant experience).
- Minimum 5 years of experience in software engineering, application development, automation, systems integration, data engineering, rapid prototyping, or related technical roles.
- Minimum 2 years of experience designing, developing, prototyping, or piloting AI-enabled, machine-learning, generative AI, automation, or intelligent workflow solutions (preferred).
- Experience building applications using large language model APIs, RAG architectures, AI orchestration frameworks, MCP, Claude, Azure/OpenAI, vector search technologies, or agentic workflow patterns (strongly preferred).
- Experience with cloud platforms such as Microsoft Azure or Amazon Web Services (preferred).
- Experience with enterprise integrations, APIs, identity and access management, secure development practices, and application lifecycle management (strongly preferred).
- Experience in a law firm, legal technology provider, consulting firm, financial-services organization, or other regulated professional-services environment (preferred but not required).
- Experience working with cross-functional stakeholders and delivering technology solutions from discovery and experimentation through pilot and production deployment (required).
- Relevant certifications in cloud engineering, AI, software development, security, automation, Agile delivery, or legal technology (preferred but not required).
Technologies
- Generative AI; Model Context Protocol (MCP); Azure/OpenAI; Large Language Model (LLM); Claude; Microsoft CoPilot; prompt engineering; retrieval-augmented generation; embeddings; vector databases; AI agents; model evaluation; responsible AI practices
- APIs; microservices; web applications; databases; authentication; authorization; logging; monitoring; testing; CI/CD practices
- Workflow platforms; robotic process automation; low-code/no-code development tools; integration platforms
- Agile; Kanban; rapid prototyping; product discovery; Python; JavaScript/TypeScript; C#; ASP.NET Core; SQL; SDKs; orchestration frameworks; cloud services; identity and access management; Amazon Web Services; vector search technologies
Location and Work Details
- Location: Washington, DC (onsite). Additional locations referenced for this posting: Boston, Philadelphia, New York, and Washington, D.C.
- Time type: Full time.
Salary: USD 140,000 - 175,000 per year. The posting notes that the salary range for Boston, New York, and Washington, D.C. is between $140,000.00 and $175,000.00 annually, with actual compensation based on job-related knowledge, skills, experience, and location.
