Senior Forward Deployed Engineer

Caylent

12h•$136,000 - $216,000•Remote

About The Position

Caylent is an AI-first cloud services company that helps organizations turn ambitious ideas into meaningful business impact. As an AWS Premier Tier Services Partner and a charter member of Anthropic’s Claude Partner Network, we combine deep expertise in AWS, artificial intelligence, and Anthropic’s Claude platform to help customers modernize their technology, build intelligent products, and move AI from experimentation into production. Our capabilities span generative and agentic AI, cloud migration and modernization, cloud-native application development, data and analytics, DevOps, managed services, security and compliance, and customer experience transformation. At Caylent, our people always come first. We are a fully remote global company with employees in Canada, the United States and Latin America. We celebrate the culture of each of our team members and foster a community of technological curiosity. Come talk to us to learn more about what it means to be a Caylien! The Mission Caylent's Anthropic Business Unit is a dedicated AI services practice built in partnership with Anthropic — Anthropic's first pure-play delivery partner. Engagements are production-grade: agents, data products, AI-augmented operations, workforce transformation. Senior FDEs run their own accounts — full relationship, from discovery through close, without anyone above managing the engagement. You scope, architect, build, and close. You are the account. We hire into two specializations: Technology-Workforce FDEs run solo technical engagements in engineering and IT organizations, owning architecture decisions and LLM-native delivery end-to-end; Operational FDEs lead single-function AI adoption programs across business workforces — persona discovery, role-specific enablement, and workflow automations deployed and owned by you.

Requirements

5+ years of engineering or technical delivery experience with meaningful time in embedded or client-facing contexts
Proven solo account delivery: evidence you've owned a client relationship from kickoff through close without supervision
Hands-on depth in one or more of: LLM application development, cloud-native architecture (AWS preferred), backend systems at scale, or enterprise business automation
Demonstrated ability to make independent technical decisions and manage your own delivery quality inside client environments
Strong communicator: technically precise with engineers, clear and confident with VP-level leadership; adjusts depth without losing accuracy
High tolerance for ambiguity; consistently delivers value before all requirements are defined

Nice To Haves

Experience building production AI systems: RAG pipelines, agents, fine-tuned models, or LLM-native applications
Hands-on with Claude, AWS Bedrock, or equivalent — model parameters, prompt architecture, tool use
Background in a consulting firm, systems integrator, or professional services environment
Familiarity with SOW-based delivery and scope management
AWS certifications: Solutions Architect Professional, DevOps Engineer Professional, or equivalent
Background in management consulting, enterprise SaaS implementation, or a business function you know deeply from the inside
Experience designing and running AI enablement programs for non-technical business audiences
Hands-on with Zapier, Power Automate, Airtable, or similar; familiarity with enterprise systems like Salesforce, Workday, ServiceNow
Track record working cross-functionally — comfortable in Finance and Legal and Operations in the same engagement

Responsibilities

Own the full client relationship on your account from discovery through close
Make architecture and build decisions appropriate to the client's environment and constraints; stand behind them
Run discovery, architecture reviews, and stakeholder interviews independently; translate ambiguous problems into scoped, deliverable work
Identify scope creep and manage it — surface risks before they become problems
Identify and surface expansion opportunities
Transfer capability that lasts: documented, runnable, maintainable software or automations that work after you leave
Contribute IP back to the practice after every engagement: patterns, templates, and reusable components