Senior AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and develop the runtime for agent planning, execution cycles, tool invocation, state management, persistent execution, and failure recovery.

• Create secure access layers for platform data and external systems.

• Architect coordination, delegation, and handoff processes for agents and workflows.

• Ensure agent behavior is version-controlled, testable, quantifiable, and safe from regression.

• Develop reusable components for the configuration of new agents.

• Transform domain-specific workflows into operational agents with established objectives, actions, execution sequences, failure management, and success metrics.

• Base agent decisions and outputs on authoritative enterprise data.

• Implement human-in-the-loop approval mechanisms, override capture, uncertainty management, and decision evidence.

• Utilize user corrections and overrides to enhance agent performance.

• Create evaluation frameworks for multi-step behaviors and define metrics for production quality, reliability, latency, cost, and interventions.

• Establish guardrails, fallback options, timeouts, cost limits, observability, and tracing measures.

• Design protections against prompt injection, unsafe tool usage, excessive permissions, data leaks, and other security concerns related to agents.

• Oversee prompt evolution, model drift, and non-determinism throughout releases.

• Integrate agents with platform APIs and third-party enterprise solutions.

• Construct retrieval and context pipelines to ensure reliable, permission-aware enterprise data access.

• Design automated execution paths with traceable audit trails.

• Build and manage AWS backend services.

• Take ownership of significant system architecture and contribute to technical decision-making.

• Participate in infrastructure-as-code and deployment pipeline initiatives.

⛳️ Requirements

• Over 6 years of experience in software engineering, particularly with production systems.

• Proven experience in building production-level LLM systems featuring tool-utilizing or multi-step agentic workflows.

• Strong grasp of LLM behavior, its limitations, and potential failure modes.

• Familiarity with LLM APIs, tool and function invocation, and planning and execution cycles.

• Experience in evaluating and troubleshooting non-deterministic systems.

• Solid background in backend and cloud technologies, particularly with AWS or similar platforms.

• Proficient in TypeScript and/or Python programming languages.

• Comfortable debugging distributed and non-deterministic systems.

• Able to balance trade-offs among accuracy, latency, reliability, and cost.

• Capable of navigating ambiguous problem domains.

• Comfortable managing production systems comprehensively.

• Able to select traditional software solutions when AI is not suitable.

• Nice to have: Experience with C# and the Microsoft .NET Framework.

• Nice to have: Familiarity with MCP and related agent/tool protocols.

• Nice to have: Experience with agentic evaluation pipelines and metrics.

• Nice to have: Background in regulated or domain-intensive systems.

• Nice to have: Knowledge of retrieval and grounding methodologies.

• Nice to have: Experience with workflow and durable-execution platforms such as Temporal, Step Functions, or n8n.

• Nice to have: Skills in containerization and orchestration using ECS, EKS, or Kubernetes.

• Nice to have: Proficiency in infrastructure as code using Terraform or similar tools.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• Supportive and inclusive work environment.