Senior Forward Deployed AI Engineer (GenAI, AWS)

Accountabilities: Embed directly within client teams to understand their operational workflows, business constraints, and objectives before designing and implementing AI-powered solutions. Rebuild and optimize business functions from first principles, collaborating with client stakeholders and forward-deployed leadership to translate complex problems into effective technical solutions. Design, develop, test, and deploy production-grade generative AI and agentic systems using Claude, AWS, and other relevant technologies, ensuring reliability, scalability, and operational readiness. Own the entire delivery lifecycle, from problem discovery and solution architecture to implementation, evaluation, deployment, and continuous improvement. Develop and maintain evaluation frameworks for non-deterministic AI systems, defining meaningful performance metrics and validating system quality against real-world requirements. Leverage existing industry blueprints and proven implementations as starting points for new engagements, incorporating lessons learned into reusable tools, frameworks, and delivery practices. Deliver solutions across AI workflow activation, agentic software development lifecycle (SDLC) initiatives, and industry-specific implementations, particularly in financial services and healthcare. Participate in pre-sales activities, technical discovery, and solution scoping, communicating effectively with senior business and technology stakeholders. Contribute to the evolution of enterprise AI delivery methodologies, engineering standards, and reusable platforms that support scalable adoption of generative AI. Share technical knowledge and strengthen professional visibility through open-source contributions, technical publications, conference presentations, and collaboration with experienced AI engineers. Requirements: 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. Benefits: Competitive compensation: Base salary of $180,000–$200,000 per year, plus performance-related bonuses, with on-target earnings (OTE) of up to $250,000. Full-time employment: Opportunity to work on challenging enterprise AI projects with direct business impact. Remote work: Primarily remote work, with on-site visits to client facilities and the New York City office approximately once per week. Flexible time off: Unlimited vacation policy. Comprehensive healthcare: Generous medical, dental, and vision insurance coverage. Retirement savings: 401(k) plan with employer matching. Advanced AI technology: Opportunities to work with frontier Claude models, AWS services, and production-grade generative AI systems. Professional development: Collaboration with experienced AI engineers, access to technical learning opportunities, and support for relevant certifications. Technical visibility: Opportunities to contribute to open-source projects, publish technical work, and participate in industry conferences and events. End-to-end ownership: Autonomy to shape solutions, influence technical decisions, and see projects through to production. Cross-industry experience: Exposure to diverse business challenges and opportunities to build transferable expertise across multiple domains. Important eligibility note: Visa sponsorship is not available.