Forward Deployed AI Engineer

Job Description

Forward Deployed AI Engineer

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Location: New York, NY

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Compensation: $180-200K + Bonus

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US Citizens only; No Visa Sponsorship

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Candidates must be local

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Responsibilities:

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• Partner with stakeholders to identify operational friction, map complex systems, and translate business challenges into clear, measurable AI use cases.

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• Define both long-term technical visions and immediate, high-impact MVPs to validate value quickly.

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• Design, code, and deploy Generative AI solutions, AI agents, and automated workflows integrated with enterprise APIs, databases, and applications.

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• Implement robust human-in-the-loop mechanisms, fallback controls, and enterprise-grade security and governance.

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• Collaborate directly with software teams to scale prototypes into reliable, production-ready systems.

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• Leverage coding agents and modern AI-driven development workflows (specification-driven development, context management) to accelerate delivery.

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• Convert custom deployment patterns into reusable assets, reference architectures, and paved-road tools to inform the broader enterprise AI roadmap.

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• Establish frameworks to measure model performance, UX, latency, cost, and business impact.

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• Implement testing, monitoring, and controls to mitigate failure modes and comply with security, privacy, and responsible AI policies.

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• Communicate complex technical concepts to non-technical stakeholders and executive leadership.

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• Influence cross-functional decisions without direct authority and mentor partner teams through digital transformation.

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Qualifications

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• 5+ years in software engineering, solution architecture, or technical consulting with a track record of shipping end-to-end products.

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• Fluency in software engineering (backend, web, mobile, distributed systems, or API/workflow orchestration) with practical experience using coding agents in structured workflows.

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• Demonstrated capability to analyze end-to-end systems, articulate technical tradeoffs, and influence cross-functional decisions without direct authority.

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• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

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Preferred

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• Experience building with LLMs, RAG, vector databases, tool calling, Model Context Protocols, or frameworks like LangGraph, LangChain, Temporal, or LlamaIndex.

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• Hands-on experience with AI evaluation metrics, observability tools, and responsible AI safeguards (human-in-the-loop).

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• Track record of driving technology adoption within financial services or other highly regulated industries.

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