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# Forward Deployed AI Engineer II

- **Company:** Secure Identity, LLC.
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $180,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Computer Programming, Information Engineering, Python (Programming Language), Machine Learning, Software Engineering, Data Logging, Application Enhancement Tool, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Backend, Agentic-AI, Low Latency, Data Management
- **Published:** October 8, 2026
- **Apply:** https://job-boards.greenhouse.io/clear/jobs/8259786

## About the Role

* 2+ years of experience in software engineering, AI engineering, machine learning engineering, data engineering, or related technical roles
 * Hands-on experience building with LLMs, AI agents, RAG, model APIs, prompt engineering, or AI application frameworks
 * Strong programming skills in Python and/or another modern backend language
 * Experience building and deploying production systems with APIs, data platforms, cloud infrastructure, logging, monitoring, and testing
 * Ability to work directly with business teams to understand ambiguous workflows and turn them into usable AI products
 * Strong product judgment and ability to identify practical, high-ROI AI use cases
 * Understanding of responsible AI concepts, including evals, guardrails, data privacy, security, human oversight, and model governance
 * Ability to communicate complex technical concepts to technical, non-technical, and executive stakeholders
 * Comfort operating in fast-paced, ambiguous environments with strong ownership from idea to impact
 * Passion for building AI systems that are practical, secure, measurable, and user-centric

## Description

* Discover, prioritize, and build AI use cases across internal tools, employee workflows, and customer-facing product features
 * Partner with Product, Engineering, Data, Security, Legal, Compliance, and Operations to translate business needs into AI-driven solutions
 * Rapidly prototype AI agents, LLM applications, RAG workflows, automation tools, and product experiences
 * Productionize validated AI use cases with strong evaluation, monitoring, logging, fallback paths, and operational ownership
 * Build reusable patterns for prompt management, retrieval, tool use, evals, guardrails, and human-in-the-loop workflows
 * Implement responsible AI best practices, including privacy, security, model governance, risk review, and customer impact assessment
 * Measure and communicate AI impact across adoption, quality, cost reduction, productivity, customer experience, and business outcomes

How you'll measure success:

 * Number of high-impact internal and customer-facing AI use cases launched
 * Adoption and measurable business impact of AI-powered tools and features
 * Quality, reliability, latency, and safety of deployed AI systems
 * Reduction in manual work, operational cost, or customer support volume
 * Improvement in customer experience, containment, accuracy, or workflow efficiency
 * Percentage of AI use cases with clear owners, evals, monitoring, and governance controls
 * Speed from AI opportunity identification to prototype, pilot, and production launch