Agentic AI Engineer — Production‑Grade, Safe & Scalable

O.C. Tanner; Salt Lake City (UT); On-site; USD 120,000 - 170,000; Full time

Job summary

O.C. Tanner is seeking an Applied AI Engineer to turn AI capability into secure, governed production systems that drive real value in user workflows.

You will work at the intersection of software engineering, AI platform engineering, and responsible AI, partnering with Product, UX, Design, Architecture, Security, and Engineering to build useful and safe AI experiences. You will design, deploy, and operate agentic AI systems with orchestration, memory, tool calling, and robust evaluation,

Qualifications

• 5+ years of software engineering experience with strong Python proficiency.
• 2+ years building production ML or agentic AI systems.
• 1+ years hands‑on experience with agentic frameworks (LangGraph, CrewAI, AutoGen, or equivalent).
• Built production AI systems including agents, MCP servers, multi‑step reasoning, and multi‑turn conversation.
• Deployed RAG systems including embedding models, vector databases, hybrid search, and retrieval optimization.
• Designed LLM strategies covering tool calling, structured outputs, prompt engineering, and context window management.
• Implemented AI safety and evaluation pipelines covering bias detection, PII leakage, faithfulness scoring, toxicity, and prompt injection mitigation.
• Optimized models for inference efficiency, latency, and cost management.

Responsibilities

• Design, build, deploy, and support production‑grade agentic AI systems that operate against explicit goals, constraints, policies, and guardrails.
• Build agent orchestration patterns for multi‑step workflows, tool calling, MCP servers, state management, memory, retries, recovery paths, and human‑in‑the‑loop controls.
• Partner closely with Product, UX, Design, Architecture, Security, and Engineering teams to create AI experiences that are useful, understandable, reliable, and aligned with real user workflows.
• Design user‑centered AI interactions, including conversational flows, feedback loops, confidence handling, explainability, graceful failure modes, escalation paths, and clear boundaries for autonomous behavior.
• Develop and operate RAG systems that ground model behavior in enterprise knowledge, including ingestion, chunking, embeddings, vector and hybrid retrieval, reranking, retrieval evaluation, and citation or traceability strategies.
• Define and implement evaluation frameworks for AI systems, including offline test sets, regression suites, adversarial testing, groundedness and faithfulness scoring, task completion metrics, and production quality monitoring.
• Instrument agentic systems for observability, including traces of model calls, prompts, tool usage, decisions, retrieved context, latency, cost, errors, and user feedback.
• Establish safeguards for responsible AI use, including prompt injection defense, data access controls, PII protection, bias and toxicity detection, misuse prevention, audit logging, and policy enforcement.
• Optimize model selection, prompts, context windows, caching, routing, inference patterns, latency, throughput, reliability, and cost across production workloads.
• Mentor engineers on applied AI practices, including prompt and context engineering, agent design, RAG, evaluation, safety, observability, and production support.
• Stay current with emerging AI platforms, frameworks, models, and standards.

Skills

Python

Software engineering

ML systems

Agentic frameworks

RAG systems

LLM strategies

AI safety & eval

Performance optimization

Education

Bachelor's degree

Tools

LangGraph

CrewAI

AutoGen

LangChain

Kafka

AWS Bedrock

Terraform

OpenTelemetry

Job description

O.C. Tanner is seeking an Applied AI Engineer to turn AI capability into secure, governed production systems that drive real value in user workflows.

You will work at the intersection of software engineering, AI platform engineering, and responsible AI, partnering with Product, UX, Design, Architecture, Security, and Engineering to build useful and safe AI experiences. You will design, deploy, and operate agentic AI systems with orchestration, memory, tool calling, and robust evaluation,