OverviewLocation: Boston or New York City
Practice: SPACE (Digital and Artificial Intelligence)
About the Role
Arthur D. Little (ADL) is seeking a Consultant - Forward Deployed AI Engineer to join our SPACE team. This is a highly hands-on role for an artificial intelligence practitioner who combines strong engineering skills with the ability to work directly with clients.
The role is about building: rapidly developing prototypes to test ideas and demonstrate value, then turning successful prototypes into robust solutions that operate at enterprise scale. You should be equally comfortable writing code, working through an ambiguous client problem, and explaining your solution to technical and business stakeholders.
Responsibilities
What You Will Do
- Work directly with clients to translate business problems into technical solutions.
- Rapidly prototype artificial intelligence and machine learning applications to test feasibility and business value.
- Take successful prototypes into production, applying sound software engineering practices for scalability, reliability, security, and maintainability.
- Design, build, test, and deploy solutions using generative artificial intelligence, artificial intelligence agents, retrieval-augmented generation, machine learning, and other appropriate approaches.Integrate artificial intelligence solutions with enterprise data, applications, workflows, and existing technology environments.
- Evaluate models, architectures, and technologies based on performance, cost, reliability, and business requirements.
- Work side-by-side with ADL colleagues, client technical teams, and external technology partners.
- Communicate technical approaches, trade-offs, results, and recommendations clearly to both technical and business audiences.
Qualifications
What We Are Looking For
- Experience: Typically 2-5 years of professional experience in artificial intelligence, machine learning, software engineering, data science, or related technical roles, with demonstrated hands-on experience building and deploying artificial intelligence solutions. Experience in consulting, professional services, or other client-facing environments is a plus.
- A hands-on builder: Strong programming skills and demonstrated experience personally developing artificial intelligence or machine learning solutions.
- Prototype-to-production capability: Able to move quickly from an idea to a working prototype - and then engineer it into a scalable production solution.
- Modern artificial intelligence expertise: Practical experience with large language models, artificial intelligence agents, retrieval-augmented generation, model evaluation, machine learning, and related technologies.
- Strong software engineering fundamentals: Experience with Python, application programming interfaces, system integration, testing, version control, cloud environments, deployment, and monitoring.
- Client orientation: Comfortable working directly with clients, asking the right questions, navigating ambiguity, and explaining complex technical topics clearly.
- Pragmatism and curiosity: Able to learn new technologies quickly and select the right approach for the problem rather than defaulting to a particular tool or framework.
Relevant technologies may include PyTorch, Hugging Face, LangChain, Databricks, Microsoft Azure, Amazon Web Services, Google Cloud, vector databases, or similar platforms. Specific technologies are less important than demonstrated ability to learn and build.
