Caylent is a cloud native services company that helps organizations bring the best out of their people and technology using Amazon Web Services (AWS). We provide a full-range of AWS services including workload migrations and modernization, cloud native application development, DevOps, data engineering, security and compliance, and everything in between.
At Caylent, our people always come first. We are a global company and operate fully remote 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!
Caylent’s Anthropic Business Unit is a dedicated AI services practice built in partnership with Anthropic. We are Anthropic’s first pure-play delivery partner.
You are the technical engine of AI engagements. You own the hands-on delivery: rapid prototyping, running evaluations, configuring Claude Code tooling, and building production- grade AI systems in client environments. You live inside your clients’ codebases, standups, and architecture decisions, and you own the technical outcomes.
There are two FDE archetypes:
Technology-Workforce FDE. Targets engineering, product, and IT organizations. Specializes in AI-enabled developer tooling, AIOps, and LLM-native product builds.
Operational FDE. Targets operational and business-unit workforces. Specializes in workforce automation, process transformation, and AI-augmented business operations.
Technical Delivery
- Own the technical delivery within AI engagements, working alongside the strategy and architecture lead
- Build rapid prototypes that validate AI approaches early. Prove feasibility before committing to full implementation
- Design and execute evaluation frameworks: define metrics, run evals against client use cases, and use results to iterate on solutions and inform strategic recommendations
- Configure and customize Claude Code tooling tailored to each client’s codebase, coding standards, and development practices
- Design and build production-grade AI systems: agents, data pipelines, AI-augmented workflows, and platform capabilities in the client’s codebase, not a sandbox
- Own the technical relationship with client engineering teams: you are the primary technical contact from IC to engineering leadership, building the trust that earns you a seat in hard conversations
- Run technical discovery sessions, architecture reviews, and hands-on workshops with engineering stakeholders; translate strategic direction into scoped, deliverable work
- Surface technical risks and opportunities. Your field observations shape the engagement strategy
- Transfer lasting capability: build as if you’re handing off tomorrow, with documentation, runbooks, and working software that stands on its own after you leave
- Feed the practice: contribute reusable patterns, evaluation templates, and field-tested IP back to the team at engagement close. This is how the business gets smarter from your
engagements
Internal Contribution
- Support pre-sales scoping and technical discussions alongside the account team
- Mentor junior engineers and contribute to the delivery methodology
- Collaborate with the engagement team to refine delivery patterns and improve handoffs between strategy and implementation
Required
- 5+ years of software engineering, with meaningful time in a client-facing or embedded delivery context
- Hands-on experience with Claude Code or equivalent AI-assisted development tools, including configuration, prompt-based instructions, and workflow automation.
- Hands-on depth in one or more of: LLM application development, cloud-native architecture (AWS preferred), Kubernetes, or backend systems at scale
- Experience with rapid prototyping. You can take an ambiguous problem and have a working proof-of-concept in days, not weeks
- Familiarity with evaluation frameworks for AI systems: defining metrics, running evals, and using results to iterate on solutions
- Proven ability to run independently inside a client environment, managing your own priorities, stakeholders, and delivery quality while aligning with the broader engagement strategy
- Strong communicator: technically precise with engineers, clear and confident with technical leadership; conceptual and easy to understand for the business; adjusts depth to the audience
- High tolerance for ambiguity; able to start delivering value before every requirement is defined
Preferred
- Experience building production AI systems: RAG pipelines, agents, fine-tuned models, or LLM-native applications
- Direct experience with Claude Code’s extensibility model: custom skills, hooks, MCP servers, and prompt architecture. Claude Certified Architect Certification preferred.
- Background in a consulting firm, systems integrator, or professional services environment
- Familiarity with SOW-based delivery and scope management in a professional services context
- AWS certifications: Solutions Architect Professional, DevOps Engineer Professional, or equivalent
- Experience designing and running technical workshops or enablement sessions for engineering teams
The FDEs who do well here share a specific profile:
- Earns trust fast. Client engineers invite you into hard conversations because you’ve shown you’ll be straight about trade-offs. Technical credibility and interpersonal judgment both matter.
- Proves it before you build it. You prototype quickly, run evals to validate assumptions, and use data to shape what gets built next. You don’t over-invest before the approach is proven.
- Writes code that lasts. You build as if you’re handing it off tomorrow: clean, documented, transferable. In services, you often are.
- Thinks in systems. You see how today’s technical decision creates tomorrow’s operational constraint. You zoom out before you zoom in.
- High learning rate. T-shaped, with breadth across domains and depth in at least one. Comfortable being new to something on Monday and useful by Wednesday.
- Partners well. Your field observations and technical judgment inform the engagement strategy, and you stay connected to the bigger picture rather than optimizing in isolation.
- Drives to closure. Once a problem is solved, you move to the next priority without dragging prior noise forward. Momentum matters here.
This is a poor fit if you prefer heavy process, close management, or environments where scope is fully defined before you arrive. Ambiguity is the default state here, not a temporary condition.
Why This Team- Ground floor of something real: this BU is early, well-resourced, and anchored to Anthropic. You’re writing the playbook, not inheriting one
- The work is at the frontier: LLM-native delivery, agents, AI product builds. Not catch-up projects for organizations still evaluating whether AI is real
- Autonomy with backing: minimal oversight in the field, but a strong technical bench behind you when the problem warrants it
- AI-native by default: this team uses AI in how it works, not only in what it ships. An agentic SDLC is how we move from prototype to production fast
- Outcomes, not hours: compensation and advancement tied to delivery performance and revenue contribution, not utilization
- Breadth that compounds: you’ll grow technical range across a diverse client portfolio faster than any single-company role
- Medical insurance for you and eligible dependents
- 401k plan with company match up to 4% and immediate vesting
- Competitive phantom equity
- Company-issued laptop
- Dental and vision insurance
- Term disability and life insurance
- Flexible Spending Account
- Equipment and office stipend
- Annual stipend for learning and development
- Unlimited paid time off
- 10 paid holidays
This role may require up to 50% travel, depending on business needs.
NOTE: We’re unable to provide visa sponsorship now or at any time in the future.
Base Salary Range: The expected base salary range for this position is $165,000 - $180,000 per year, commensurate with experience and qualifications.
Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.
NOTE: We’re unable to provide visa sponsorship now or at any time in the future.
At Caylent, we are committed to fair, transparent, and inclusive hiring practices. As part of our recruitment process, we may use artificial intelligence (AI) tools or automated systems to assist with the screening and evaluation of applications to help match candidate qualifications with job requirements.
These tools are designed to support — not replace — human decision-making. Final hiring decisions are always made by our trained recruitment professionals.
If an AI or automated tool is used during your application process, it will only be in accordance with applicable laws and regulations, and your information will be handled in a secure and confidential manner.
If you have any questions, please contact [email protected]
Caylent is a place where everyone belongs. We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.
We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at [email protected].Top Skills
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