Forward Deployed Engineer, Agentic Platform
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Key skills for this role
Role Overview
The role connects the North product with client engineering teams to solve complex problems and securely integrate AI into finance, healthcare, telecommunications, and other critical sectors.
The engineer owns the design, build, and deployment of agentic workflows powered by large language models from prototypes through production-grade AI agents.
Agent workflows integrate LLMs with tools, APIs, and data sources and must be reliable, observable, safe, and auditable from day one.
Key Skills for This Role
Full Job Posting
Role Overview
The role connects the North product with client engineering teams to solve complex problems and securely integrate AI into finance, healthcare, telecommunications, and other critical sectors.
The engineer owns the design, build, and deployment of agentic workflows powered by large language models from prototypes through production-grade AI agents.
Agent workflows integrate LLMs with tools, APIs, and data sources and must be reliable, observable, safe, and auditable from day one.
Responsibilities
- Translate high-value, ambiguous business problems into well-framed agentic workflows with clear success criteria and evaluation methodologies.
- Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools, APIs, and sensitive enterprise data sources.
- Build and ship features for North, the AI workspace platform, across the full product lifecycle from conceptualization through production.
- Own the scoping and shaping of use cases end to end, including work in frontend or other technical areas when needed.
- Contribute to shared frameworks and patterns that enable consistent, high-quality delivery across customers and teams.
- Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization.
- Travel up to 20–40% to work on site with customers and partners.
Requirements
- Hands-on experience building and deploying production-grade software in Python with clean, testable, observable, and scalable code.
- Experience building and deploying highly performant RAG and agentic applications, including multi-step agents using ReAct or Plan-and-Execute patterns.
- Deep familiarity with frontier models, vector databases, and orchestration frameworks.
- Proven ability to build robust evaluation frameworks that measure agent accuracy, safety, and latency.
- Experience working directly with customers and leading technical discussions with enterprise stakeholders.
- Experience owning the full scope of a use case end to end.
- Ability to execute well in fast-paced and ambiguous environments with shifting priorities.
Bonus Qualifications
- Experience setting architectural standards for AI and agentic systems across distributed teams.
- Experience working in unfamiliar technical areas, such as frontend, when the problem calls for it.
- Exposure to regulated or sensitive industry environments, including finance, healthcare, or telecommunications.
- Experience with enterprise security, compliance, or auditability requirements for AI systems.
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