Forward Deployed AI Engineer

Forward Deployed AI Engineer

Location: New York, NY

Compensation: $180-200K + Bonus

Do you have the right skills and experience for this role Read on to find out, and make your application.

US Citizens only; No Visa Sponsorship

Candidates must be local

Responsibilities:

• Partner with stakeholders to identify operational friction, map complex systems, and translate business challenges into clear, measurable AI use cases.
• Define both long-term technical visions and immediate, high-impact MVPs to validate value quickly.
• Design, code, and deploy Generative AI solutions, AI agents, and automated workflows integrated with enterprise APIs, databases, and applications.
• Implement robust human-in-the-loop mechanisms, fallback controls, and enterprise-grade security and governance.
• Collaborate directly with software teams to scale prototypes into reliable, production-ready systems.
• Leverage coding agents and modern AI-driven development workflows (specification-driven development, context management) to accelerate delivery.
• Convert custom deployment patterns into reusable assets, reference architectures, and paved-road tools to inform the broader enterprise AI roadmap.
• Establish frameworks to measure model performance, UX, latency, cost, and business impact.
• Implement testing, monitoring, and controls to mitigate failure modes and comply with security, privacy, and responsible AI policies.
• Communicate complex technical concepts to non-technical stakeholders and executive leadership.
• Influence cross-functional decisions without direct authority and mentor partner teams through digital transformation.

Qualifications

• 5+ years in software engineering, solution architecture, or technical consulting with a track record of shipping end-to-end products.
• Fluency in software engineering (backend, web, mobile, distributed systems, or API/workflow orchestration) with practical experience using coding agents in structured workflows.
• Demonstrated capability to analyze end-to-end systems, articulate technical tradeoffs, and influence cross-functional decisions without direct authority.
• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Preferred

• Experience building with LLMs, RAG, vector databases, tool calling, Model Context Protocols, or frameworks like LangGraph, LangChain, Temporal, or LlamaIndex.
• Hands-on experience with AI evaluation metrics, observability tools, and responsible AI safeguards (human-in-the-loop). xhyhwjd
• Track record of driving technology adoption within financial services or other highly regulated industries.