Forward Deployed AI Systems Engineer
About the Role
A high-impact AI engineering initiative is seeking technical talent to support the development and deployment of advanced machine learning systems in mission-critical environments. The work spans applied research, infrastructure engineering, model deployment, and operational AI systems designed for reliability and scale.
This opportunity is ideal for individuals who can operate across both experimentation and production environments while maintaining strong ownership over system performance and delivery. The role requires comfort working in technically demanding, security-conscious settings with evolving operational requirements.
The work involves building and scaling AI infrastructure, deploying agentic systems, supporting distributed inference environments, and collaborating in forward-deployed operational contexts where reliability, adaptability, and execution quality are critical.
What You'll Do
- Build and maintain data pipelines supporting model training, evaluation, and research workflows
- Design and manage reinforcement learning experimentation environments
- Develop scalable model inference systems for production workloads
- Implement SDKs and integrations across modern AI platforms and tooling ecosystems
- Build agentic AI workflows using multi-agent systems, retrieval pipelines, and orchestration frameworks
- Transition AI systems from prototype stages into stable production deployments
- Optimize distributed systems for performance, reliability, and operational scalability
- Collaborate directly with external stakeholders in forward-deployed technical environments
- Maintain security, reliability, and operational standards across infrastructure and deployment layers
Requirements
- Strong Python engineering experience with end-to-end system ownership
- Hands-on experience with LLM systems and agentic AI frameworks such as LangChain or LangGraph
- Experience building or maintaining ML infrastructure and data pipelines
- Familiarity with reinforcement learning workflows or simulation environments
- Understanding of distributed systems and inference scaling architectures
- Ability to work effectively in high-security or high-reliability operational environments
- Comfort operating independently in ambiguous or partner-facing technical contexts
- Strong debugging, systems thinking, and infrastructure troubleshooting skills
- Experience with modern AI platforms such as Vertex AI, Bedrock, or comparable ecosystems preferred
- Background in security engineering, infrastructure systems, or mission-critical environments preferred