Forward Deployed Engineer
Robots and Pencils1 day ago
Remote, United StatesStaff+
Base Salary
$177k - $210k/yr
Responsibilities
- Lead the design and implementation of complex AI/ML systems from research through production in client environments.
- Build, deploy, and evolve scalable ML platforms, pipelines, and infrastructure for reliable model development and deployment.
- Diagnose and resolve integration challenges across unfamiliar codebases, cloud environments, and organizational contexts.
- Embed with client teams, translate business problems into effective AI system designs, and drive post-delivery adoption.
- Partner with product, engineering, and leadership stakeholders and communicate technical tradeoffs to technical and non-technical audiences.
- Define AI architecture, engineering standards, responsible AI practices, and long-term technical direction for engagements.
- Mentor junior and mid-level engineers through coaching, code reviews, pairing, and technical discussions.
- Own ambiguous and high-stakes work through production while managing reliability, cost, safety, and scalability.
Requirements
- 7+ years of professional software engineering experience, including 4+ years focused on production AI/ML systems and deep hands-on generative AI development.
- Expert software engineering background using Python or a similar language, with strong scalable-system design skills.
- Deep expertise with cloud platforms, including AWS services and AWS GenAI offerings.
- Proven experience designing and shipping complex agentic systems in production, including under client or enterprise constraints.
- Mastery of AI frameworks and orchestration tools, plus strong experience with LLM application evaluation and observability.
- Deep understanding of AI safety, responsible AI, prompt injection defenses, and PII handling.
- Extensive experience building RAG pipelines, including chunking strategies, embedding models, vector databases, and advanced retrieval techniques.
- Experience designing and integrating internal and third-party APIs at scale.
- Advanced cost optimization expertise covering token economics, caching, model routing, and quantization.
- Strong working knowledge of Docker and Kubernetes for containerized deployments.
- Expert day-to-day use of AI-forward coding tools such as Claude Code and Cursor.
- Ability to operate in ambiguous, fast-moving client environments, communicate clearly, and build engineering-level trust.
Tech Stack
Categories
Forward Deployed