AI Engineer
Job Description
Join the Dechert Innovation Lab at Dechert LLP, embedded in the heart of how emerging AI moves from idea to real-world impact. This onsite role in Washington, DC focuses on discovering, evaluating, prototyping, and piloting AI-enabled technologies that can improve legal services and firm operations. You will help build proof-of-concept and pilot solutions, including generative AI, RAG, workflow automation, and intelligent agents, and then recommend transitions to enterprise teams for production and long-term support.
Compensation: USD 140,000 - 175,000 per year. At the time of this posting, the salary range for this position in Boston, New York and Washington, D.C. is between $140,000.00 – $175,000.00 annually. Actual compensation is commensurate with job related knowledge, skills, experience, and location of the position.
What you’ll do
- Partner with attorneys and cross-functional teams including practice groups, legal project management, knowledge management, finance, risk, client development, and business-services teams to identify innovation opportunities, understand workflows and pain points, and define desired outcomes.
- Lead technical discovery and innovation sessions, assessing business problems for AI, automation, and emerging technologies.
- Rapidly design, develop, and evaluate proof-of-concept and pilot solutions using approved and emerging platforms, including AI platforms, APIs, low-code tools, workflow automation platforms, and custom development technologies.
- Build and test experimental AI-enabled applications such as generative AI assistants, document and knowledge-search solutions, RAG applications, workflow copilots, intelligent agents, and decision-support tools.
- Select and evaluate technical approaches based on innovation potential, business value, complexity, data sensitivity, scalability, supportability, and time-to-value.
- Define and test success measures including feasibility, time saved, adoption potential, accuracy, user satisfaction, process-cycle reduction, risk reduction, and business impact.
- Assess pilot outcomes and recommend whether successful experiments should move into the appropriate enterprise application teams.
- Stay current with AI engineering practices, legal-industry AI use cases, emerging tools and platforms, AI governance requirements, and technology trends, and recommend new technologies for future evaluation.
- Contribute to intake prioritization, solution estimation, innovation pipeline planning, vendor evaluations, and portfolio reporting.
- Other responsibilities as needed.
What you bring
- Experience with Generative AI and related tooling and concepts including Model Context Protocol (MCP), Azure/OpenAI, LLM, Claude, Microsoft CoPilot, prompt engineering, retrieval-augmented generation, embeddings, vector databases, AI agents, model evaluation, and responsible AI practices.
- Application development concepts covering APIs, microservices, web applications, databases, authentication, authorization, logging, monitoring, testing, and CI/CD practices.
- Automation and orchestration technologies such as workflow platforms, robotic process automation, low-code/no-code development tools, and integration platforms.
- Software development methodologies including Agile, Kanban, rapid prototyping, product discovery, and iterative delivery.
- Strong software engineering skills in one or more modern programming languages: Python, JavaScript/TypeScript, C#, ASP.NET Core, SQL, or similar.
- Ability to translate ambiguous business needs into testable hypotheses and experiment designs.
- Strong consultative and communication skills for working with attorneys, business leaders, technical teams, vendors, and nontechnical users.
- Strong analytical, problem-solving, and systems-thinking abilities, with an emphasis on balancing speed and learning with security, quality, governance, maintainability, and long-term supportability.
- Comfort working with ambiguity and multiple concurrent initiatives, with resilience across iterative experimentation and learning from unsuccessful outcomes.
- Interest in working directly with end users to test solutions.
- Interest in responsible AI, data protection, human-centered design, and practical technology governance.
- Bachelor’s degree in a relevant technical discipline required (Computer Science, Software Engineering, Information Systems, Data Science, Artificial Intelligence, or related). Equivalent combination of education, training, and relevant experience may be considered.
- 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.
Preferred experience
- Experience building applications using large language model APIs, RAG architectures, AI orchestration frameworks, Model Context Protocol (MCP), Claude, Azure/OpenAI, vector search technologies, or agentic workflow patterns.
- Experience with cloud platforms such as Microsoft Azure or Amazon Web Services.
- Experience with enterprise integrations, APIs, identity and access management, secure development practices, and application lifecycle management.
- Experience in a law firm, legal technology provider, consulting firm, financial-services organization, or other regulated professional-services environment is preferred but not required.
- Experience delivering technology solutions from discovery and experimentation through pilot and production deployment with cross-functional stakeholders required.
- Relevant certifications in cloud engineering, AI, software development, security, automation, Agile delivery, or legal technology are preferred but not required.
Location: Boston, Philadelphia, New York and Washington, D.C. (onsite). Time type: Full time.