AI Engineer jobs in Boston, MA

Develop and test full stack, cloud-native applications on AWS, translating client needs into solutions across architecture, design, implementation, and testing. Troubleshoot application and platform issues, apply AI-enabled engineering methods, collaborate with engineering teams, and review work while mentoring junior colleagues.

Build and own the production AI agent for the Luma platform, including its reasoning loop, tools, memory, security controls, recovery, and evaluation. Develop the surrounding services and AI-first engineering workflow, and improve agent reliability, performance, and safe delivery in collaboration with product teams and scientists.

Provide senior technical leadership for Analytics Engineering, shaping data foundations, modeling standards, architecture, governance, quality, tooling, and developer experience. Build trusted canonical datasets, semantic layers, and AI-enabled analytical tools that support self-service analytics and improve decision-making across the company.

You will design, implement, and deploy scalable AI solutions while partnering with clients across various industries to address complex business challenges. Additionally, you will provide thought leadership in scientific communities and guide non-technical teams in software development best practices.

The Data Engineer will build and maintain low-level data pipelines using Databricks and Apache Spark while coordinating with onshore and offshore teams. They are also responsible for supporting deployment, post-production maintenance, and communicating project status to engagement managers.

Drive technical wins for complex Cloud AI workloads by supporting the business cycle from evaluation through customer ramp. Provide deep technical consultation and develop prototypes to secure buy-in from customer domain experts.

You will design and deploy complex AI-driven agentic workflows while providing technical leadership and mentorship to the engineering team. Additionally, you will own the end-to-end lifecycle of services, ensuring system reliability, security, and efficient cloud infrastructure management.

Design, develop, and maintain software components across a modern cloud-based platform while participating in the full development lifecycle. Partner with cross-functional teams to deliver scalable, high-quality solutions and explore emerging technologies like AI-assisted development.

The SDE 3 will design and deploy multi-agent AI workflows while owning the end-to-end lifecycle of complex services and integrations. They will also provide technical leadership by mentoring junior engineers and driving internal AI adoption strategies.

The role involves designing and securing AI-enabled products and cloud environments using Zero Trust principles and secure software development lifecycles. You will collaborate with stakeholders to implement production-quality AI security architectures and automated threat management capabilities.

The engineer will design and implement secure architectures for generative and agentic AI, applying Zero Trust controls across cloud environments and development pipelines. They will also lead client discovery sessions and develop production-quality AI security platforms while mentoring team members.