ProEdge Services
AI

Senior Applied AI Agentic Systems Engineer Remote – US

ProEdge Services ·

Actively hiring Posted about 4 hours ago

Role overview

We are looking for a senior engineer to design, build, and productionize agentic AI systems and LLM-powered workflows for mission‑critical, real‑world use cases. This is a fully remote role based in the US.

What you'll work on

  • Build agentic AI systems
  • Design and implement tool‑calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP or similar protocols.
  • Engineer robust guardrails for safety, compliance, and least‑privilege access across tools and data sources.

  • Productionize LLMs

  • Build evaluation frameworks for open‑source and proprietary LLMs.

  • Implement retrieval pipelines, prompt synthesis, response validation, and self‑correction loops tailored to production operations.

  • Integrate with runtime ecosystems

  • Connect agents to observability, incident management, and deployment systems.

  • Enable automated diagnostics, runbook execution, remediation, and post‑incident summarization with full traceability.

  • Collaborate directly with users

  • Partner with production engineers and application teams to translate production pain points into agentic AI roadmaps.

  • Define objective functions linked to reliability, risk reduction, and cost, and deliver auditable, business‑aligned outcomes.

  • Safety, reliability, and governance

  • Build validator models, adversarial prompts, and policy checks into the stack.

  • Enforce deterministic fallbacks, circuit breakers, and rollback strategies.

  • Instrument continuous evaluations for usefulness, correctness, and risk.

  • Scale and performance

  • Optimize cost and latency via prompt engineering, context management, caching, model routing, and model distillation.

  • Leverage batching, streaming, and parallel tool‑calls to meet stringent SLOs under real‑world load.

  • RAG and knowledge systems

  • Design and maintain robust RAG pipelines, including domain‑knowledge curation and data‑quality validation.

  • Establish feedback loops and milestone frameworks to maintain knowledge freshness over time.

  • Raise the bar

  • Drive design reviews, experimentation rigor, and high‑quality engineering practices.

  • Mentor peers on agent architectures, evaluation methodologies, and safe deployment patterns.

What we're looking for

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Seniority level

Associate

Employment type

Full-time

Job function

Information Technology

Industries

IT Services and IT Consulting

Tags & focus areas

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