Senior Forward Deployed Engineer

Main Responsibilities:

• Architect and develop production AI / agentic systems optimized for business use cases, including agent infrastructure and integrations with client infrastructure

• Manage AI product development roadmap

• Rapid testing and evaluation of agentic systems, including reliability engineering, performance measurement and cost management

• Continuously interface with clients to understand areas for transformation and co-design AI and security best practices

Required experience and qualifications:

• BS in Computer Science or closely-related field

• 3+ years of relevant industry experience or equivalent

• Direct experience shipping an AI or agentic AI system end-to-end to users, preferably owned or led the project

• Excellent communication skills, particularly in communicating technical concepts in an approachable way to clients

• Proficiency in Python

• Strong production maturity and system design skills

• Familiarity with agentic tooling and development, including Model Context Protocols (MCPs), agent skills, agent orchestration, Retrieval Augmented Generation (RAG), etc.

• Experience designing evals, observability and monitoring for AI, plus debugging failure modes in production

• Knowledge of enterprise security best practices to securely deploy AI and software

• Proficiency in building data pipelines and API integrations

• Familiarity with cloud platform (AWS (preferred)/Azure/GCP), infrastructure as code, containerization

• Passion for experimenting with AI models, open-source repos, etc.

• Knowledge of latest developments in AI capabilities and deployment strategies

Good to haves

• MS or PhD in Computer Science or related field — or equivalent depth from industry

• 5+ years of relevant industry experience or equivalent

• Experience deploying AI in a specific vertical or business use case

• Ability to identify and articulate business value from AI deployments — including ROI framing, process mapping, and stakeholder alignment

• Familiarity with enterprise software ecosystems, including Oracle SAP, Microsoft, etc.

• Proficiency in additional languages, such as TypeScript, SQL, Java, Go

• Familiarity with data privacy practices for AI

• Experience with on-device or on-prem data management or AI deployment.

• Familiarity with ML frameworks such as PyTorch, TensorFlow, etc.