AI Engineer - Agentic Systems & LLMs

Reveal Technology is a dynamic startup revolutionizing field operations by providing software tools and insights to individuals in remote environments. They are seeking an AI Engineer to design and build an agentic intelligence layer that enables software to progressively assume responsibility while remaining transparent and aligned to doctrine and policy.

Responsibilities:

• Design and implement production-grade LLM and agentic systems that ingest operational, doctrinal, and policy data and transform it into structured tasks, workflows, and resource-aware plans
• Build orchestration layers across workflows, tools, and human approvals to support a recommendation-first AI copilot with progressive, user-authorized agentic actions
• Implement RAG pipelines over doctrine, regulations, and historical data to enable constraint-aware reasoning, sequencing logic, and transparent, explainable recommendations
• Design trust, permissioning, and rollback mechanisms that adapt system autonomy based on user behavior, experience, and operational risk
• Instrument systems for auditability, traceability, and user trust, ensuring all outputs can be explained and linked back to source inputs
• Optimize AI systems for latency, cost, reliability, and explainability in real-world operational environments
• Collaborate closely with product, UX, engineering, and domain experts to translate complex operational workflows into scalable, human-centered AI systems

Requirements:

• 5-10 years' relevant experience in AI/LLM
• Strong hands-on experience with developing and deploying LLM-based systems in production
• Experience building multi-step agentic AI systems
• Experience in MLOps, automating the process of training and deploying models and supportive architecture
• Must have experience with containerization approaches such as Docker and Kubernetes
• Developed CI/CD pipelines for testing and automation
• Experience in developing or utilizing third party solutions to evaluate and quantify model performance
• Proficiency in Python
• Experience with: LLM orchestration, RAG architectures, Function/tool calling, State management across AI workflows, Vector Databases
• Ability to reason about constraints, optimization, and dependencies
• Comfort operating in ambiguous, fast-moving product environments
• Experience with planning, scheduling, or optimization systems
• Experience with policy-driven or regulated environments
• Familiarity with trust modeling, human-in-the-loop systems, or safety rails
• Prior work on systems where AI actions had real-world consequences
• Willingness to engage deeply with users and iterate based on behavior, not theory