Forward Deployed Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of the design and execution of intricate ML/AI systems from start to finish within client settings, making architectural decisions and guiding solutions from research to large-scale production.

• Construct, deploy, and enhance scalable ML platforms, pipelines, and infrastructure that facilitate dependable and repeatable model development and deployment, often within pre-existing client frameworks.

• Identify and resolve integration issues in live systems, quickly adapting to unfamiliar codebases, cloud environments, and organizational structures.

• Set benchmarks for AI-driven engineering by skillfully utilizing tools such as Claude and Cursor, while assisting both our team and client teams in their effective adoption.

• Collaborate closely with client teams, swiftly earning their trust and transforming their business challenges into functional AI system designs tailored to their specific environments.

• Work in partnership with product, engineering, and leadership teams—both ours and the client's—to ensure alignment between technical direction and business results.

• Simplify complex AI trade-offs, risks, and opportunities into understandable narratives for both technical and non-technical audiences.

• Lead design evaluations and technical discussions, enhancing the engineering standards across both R&P and client teams.

• Establish AI architecture and engineering benchmarks for each project, providing insights on trade-offs, long-term impacts, and responsible AI practices.

• Facilitate client adoption of AI systems after delivery by identifying knowledge gaps, creating enablement materials, and providing skills development for client engineers as needed.

• Mentor and develop junior and mid-level engineers, amplifying impact through coaching, code reviews, and collaboration on challenging issues.

• Assume responsibility for the most ambiguous and critical tasks, guiding them to production with a focus on reliability, cost efficiency, and safety.

⛳️ Requirements

• 7+ years of professional software engineering experience, with at least 4 years dedicated to AI/ML systems in production and substantial hands-on experience with generative AI development.

• Strong software engineering foundation (Python or similar) with a keen design sense for scalable and maintainable systems.

• In-depth expertise with cloud platforms, particularly a thorough understanding of AWS services and AWS GenAI offerings.

• Demonstrated success in designing and deploying complex agent-based systems in production settings, including within client or enterprise constraints.

• Mastery of AI frameworks and orchestration tools.

• Significant experience with evaluation frameworks and observability tools for LLM applications, including the development of these capabilities where they are lacking.

• Comprehensive knowledge of AI safety, responsible AI principles, prompt injection defenses, and handling of PII.

• Extensive experience in building RAG pipelines: chunking strategies, embedding models, vector databases, and advanced retrieval techniques.

• Experience in API design, including architecting and integrating with internal and third-party services at scale.

• Advanced expertise in cost optimization: token economics, caching strategies, model routing, and quantization.

• Solid working knowledge of Docker and Kubernetes for containerized deployments.

• Proven, daily usage and expert knowledge of AI-centric coding tools such as Claude Code and Cursor.

• Ability to operate comfortably in ambiguous, fast-paced client environments—quickly adapting, communicating effectively, and building trust at the engineering level.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health benefits including medical, dental, and vision coverage.

• Opportunities for professional development and skill enhancement.

• Flexible working hours and remote work options.

• Collaborative and innovative work environment.