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Mid LevelFull-timeRailsAI
Salary Range
$20,400 - $27,600 /year
This salary is estimated based on similar roles. The actual salary may vary.
Key Responsibilities
- →Own end-to-end execution of AI agent deployments from discovery and scoping through launch and optimization.
- →Configure agent workflows, decision logic, and automation behaviors to maximize accuracy, reliability, and business outcomes.
- →Implement guardrails and validation frameworks to ensure safe, compliant, and predictable agent performance.
- →Build, test, and validate integrations with enterprise systems (e.g., CRM, ticketing, telephony, data platforms).
- →Partner with customer technical stakeholders to define success criteria, gather requirements, and deliver against timelines.
- →Translate customer needs into clear implementation plans and documentation.
- →Run tight feedback loops with Engineering and Product to improve platform capabilities.
- →Collaborate with Product, Engineering, Design, and GTM teams to deliver repeatable, best-in-class deployments.
Requirements
- ✓5+ years in a technical customer-facing role (Solutions Engineering, Forward Deployed Engineering, Implementation Engineering, Technical Consulting, Technical PM, or similar).
- ✓Strong technical foundation - comfortable coding, working with APIs, and building integrations end-to-end.
- ✓Experience delivering production-grade enterprise solutions requiring testing, validation, and iteration.
- ✓Ability to communicate with senior technical stakeholders and translate requirements into execution plans.
- ✓Comfortable operating in fast-moving, ambiguous environments.
- ✓Comfortable working in EST hours (3:30 AM IST).
- ✓Even Better If You Have
- ✓Experience building with LLMs or AI agents (prompting, evaluation, guardrails, workflow design).
- ✓Experience integrating enterprise SaaS systems (CRM, ticketing, data pipelines) with attention to security and compliance.
- ✓Computer Science, Engineering, or Math degree (or equivalent experience).
- ✓Strong product instincts - ability to define success metrics and contribute customer insights to product evolution.
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