Senior Forward Deployed AI Engineer (GenAI, AWS)

As a Senior Forward Deployed AI Engineer, you will design, build, and deploy production-ready generative AI solutions for enterprise clients across financial services, healthcare, and other regulated industries.
You will work directly within client teams to understand complex business operations and transform them into practical, AI-powered systems.
Using advanced LLM technologies, including Claude, alongside AWS cloud infrastructure, you will take solutions from initial discovery to production deployment and measurable business impact.
You will have the autonomy to shape technical approaches, make critical engineering decisions, and take ownership of end-to-end delivery.
Working in an environment that values experimentation, technical excellence, and customer collaboration, you will tackle diverse challenges across industries and business functions.
You will also contribute to reusable AI frameworks, industry-specific solutions, and best practices that accelerate enterprise AI adoption.

• Typically 7+ years of professional software engineering experience, including substantial hands-on responsibility for production systems. A strong commitment to remaining actively involved in coding and technical delivery is essential.

• Proven experience deploying generative AI or large language model (LLM) applications into production, with a practical understanding of the challenges that arise beyond prototyping.

• Demonstrated ability to evaluate non-deterministic AI systems by building or owning evaluation suites, defining appropriate metrics, and explaining the rationale behind evaluation methods.

• Strong software engineering fundamentals and the ability to become productive quickly in unfamiliar codebases, programming languages, and technical environments.

• Proficiency in Python and/or TypeScript, with a focus on engineering depth, maintainability, and production-quality implementation.

• Experience designing and delivering cloud-native solutions on AWS, including operational considerations, reliability, scalability, and maintainability. Experience with GCP or Azure is an advantage.

• Hands-on experience with Claude, Claude Code, and Cowork, including skills, workflows, Model Context Protocol (MCP), integrations, connectors, and custom harnesses.

• Ability to understand unfamiliar business functions quickly, engage with end users and operators, and translate real operational needs into effective technical solutions.

• Experience in pre-sales, technical consulting, or solution discovery, with the ability to communicate credibly with senior business leaders, CTOs, and other executive stakeholders.

• Strong ownership, adaptability, and problem-solving skills, with the confidence to navigate ambiguity, define approaches independently, and drive engagements from discovery through production.

• Excellent communication and collaboration skills, particularly in environments where engineers work closely with clients and must balance technical quality with measurable business outcomes.

Nice to have:

• Experience with containerization and orchestration technologies such as Docker, Kubernetes, or Amazon ECS.

• Practical knowledge of CI/CD pipelines and production deployment automation.

• Infrastructure-as-code experience using AWS CDK, CloudFormation, or Terraform.

• Open-source contributions, technical publications, or public writing focused on applied AI and software engineering.

• Experience working with regulated industries, particularly financial services, insurance, or healthcare.