Forward Deployed AI Engineer

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

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

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

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience). \n, * Experience building with LLMs, RAG, vector databases, tool calling, Model Context Protocols, or frameworks like LangGraph, LangChain, Temporal, or LlamaIndex. \n

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

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

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

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

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

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

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

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

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

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

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

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

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

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