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Berkeley Research Group (BRG) logo
Berkeley Research Group (BRG)

Intelligence that works.

AI Product Engineer

Solutions EngineerSolutions EngineerOtherRemoteSeniorTeam 1,001-5,000H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

93 days ago

Salary

$130K - $190K / year

Seniority

Senior

Bachelor Degree5 yrs expExperience acceptedEnglishAWSAzure

Job Description

AI Product Engineer

Berkeley Research Group (BRG)

• Lead structured discovery with practice leaders/experts to understand workflows, data, pain points, and opportunities for AI-driven automation and improved deliverables. • Translate expert needs into clear product requirements, user stories, success metrics, and implementation plans to execute. • Own and maintain an AI capability roadmap focused on AI workflows, agents, and practice-specific tools aligned with BRG strategy and compliance. • Prioritize AI use cases based on impact, feasibility, risk, supportability, and measurable value (efficiency, quality, new offerings). • Drive adoption: build enablement plans, gather feedback, track usage metrics, and iterate to improve sustained value. • Design and ship production AI capabilities such as RAG, prompt/tool patterns, and agent workflows with end-to-end ownership (design → build → test → deploy → monitor). • Implement and improve retrieval quality (chunking, embeddings, hybrid/semantic ranking, prompt design) and establish evaluation approaches (offline/online testing and human-in-the-loop where needed). • Integrate Azure AI services end-to-end (e.g., Azure OpenAI, Azure AI Search, Document Intelligence, orchestration frameworks) into secure and supportable solutions. • Operationalize solutions using CI/CD, telemetry/monitoring, rollout strategies, and reliability targets (SLIs/SLOs) for production readiness. • Provide Tier III support: troubleshoot incidents, perform root cause analysis, implement fixes, and create runbooks for support handoff.

Job Requirements

  • Bachelor’s degree in IT, Computer Science, Engineering, Business, or related field (or equivalent experience)
  • ~5+ years of experience in a blend of solution delivery/architecture, AI implementation, product ownership/business analysis, or consulting-style internal enablement.
  • Strong understanding of modern AI/LLM approaches: prompt engineering, RAG, embeddings, and agents/agentic workflows.
  • Hands-on ability to build and deliver AI workflows in production and explain tradeoffs to non-technical stakeholders.
  • Strong communication and stakeholder-management skills; comfort working with senior experts in a professional services environment.
  • Preferred Azure-focused AI experience (Azure OpenAI, Azure AI Search, Document Intelligence) and/or familiarity with enterprise AI platforms.
  • Experience with MLOps/DevOps practices (CI/CD, instrumentation, rollout) for LLM apps.
  • Familiarity with compliance frameworks, AI governance and regulated data considerations.
  • Preferred Certifications (Examples) Microsoft Certified: Azure AI Engineer Associate, Microsoft Certified: Azure Solutions Architect Expert, AWS AI Practitioner, AWS Solutions Architect

Benefits

  • Health insurance
  • Retirement plans
  • Flexible work arrangements
  • Professional development

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