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84.51°

Senior Manager, AI Reliability Engineering -Kroger Technology & Digital (P2498)

84.51° · Cincinnati, OH

Posted 29 days ago

or apply directly on 84.51° 's site. We never take the application ourselves.

Is this posting real?

This role has been open
29 days
84.51° 's roles stay open a median of 31 days
Reposted
No
Salary listed
No
0% of 84.51° 's roles list one
Ghost-job risk at 84.51°
high
7 stale, 0 reposted of 19 open
Hiring momentum
31 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-09-17

Measured from postings appearing on and disappearing from 84.51° 's own greenhouse board since 2026-08-03. Full hiring picture for 84.51° .

About this role

The Senior Manager, AI Reliability Engineering at Kroger Technology & Digital will lead the establishment of a new engineering discipline focused on making enterprise AI operationally trustworthy at scale. This role involves defining standards for production-grade AI, ensuring reliability and quality in AI systems, and collaborating with various teams to embed resilience and observability into AI architectures. The manager will also oversee incident management, team development, and drive efficiency in AI operations.

Our read on this posting3.0out of 5
benefits
1/5
freshness
4/5
career value
5/5
role clarity
5/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of 84.51° as an employer.

What you need

  • Minimum 10+ years of experience in software, platform, cloud, SRE or production engineering, including 3 or more years leading engineering teams.
  • Track record of building engineering capabilities, standards, automation or platforms that measurably improved system quality and reliability at scale.
  • Strong technical depth in distributed systems, Kubernetes, cloud infrastructure on GCP and/or Azure, networking, identity, automation, CI/CD and modern observability engineering.
  • Experience establishing SLOs, error budgets, on-call practices, production-readiness reviews, incident management and post-incident improvement programs.
  • Direct experience with ML, AI or LLM systems in production, or demonstrated ability to master failure modes unique to models and agents, including drift, non-determinism, quality regression, prompt and context issues, and hallucination.
  • Ability to influence architecture and roadmaps, lead through ambiguity, partner across a matrixed organization and drive outcomes without direct authority.

Nice to have

  • Hands-on experience with LLMOps, model observability and evaluation tooling such as LangSmith, MLflow, Arize, Fiddler or custom evaluation pipelines.
  • Familiarity with agentic systems, including orchestration, tool use, MCP-based integrations, registries and their unique reliability and quality challenges.
  • Background bridging software or SRE practices with ML, data science and Responsible AI engineering cultures, including experience establishing a new engineering discipline.
  • Experience with multi-region, high-availability services, hybrid operating models and regulated or high-risk enterprise workloads.

Worth weighing

  • Role involves building a new discipline from the ground up, which may come with challenges and uncertainties.
  • No specific salary or benefits information provided in the posting.
  • The position requires a strong blend of technical and leadership skills, which may not suit all candidates.
  • The role is heavily focused on operational reliability and may involve high-pressure incident management responsibilities.

Summarised from 84.51° 's posting. Read the full original.

Listed by 84.51° on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.

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