BRG

BRG combines world-leading academic credentials with world-tested business expertise purpose-built for agility and connectivity, which sets us apart—and gets you ahead. At BRG, our top-tier professionals include specialist consultants, industry experts, renowned academics, and leading-edge data scientists. Together, they bring a diversity of proven real-world experience to economics, disputes, and investigations; corporate finance; and performance improvement services that address the most complex challenges for organizations across the globe. Our unique structure nurtures the interdisciplinary relationships that give us the edge, laying the groundwork for more informed insights and more original, incisive thinking from diverse perspectives that, when paired with our global reach and resources, make us uniquely capable to address our clients’ challenges. We get results because we know how to apply our thinking to your world. At BRG, we don’t just show you what’s possible. We’re built to help you make it happen. BRG is proud to be an Equal Opportunity Employer.

AI Product and Solutions Engineer

LLM EngineerMachine Learning EngineerFull TimeRemoteTeam 1,001-5,000

Location

United States

Posted

3 days ago

Salary

$130K - $190K / year

No structured requirement data.

Job Description

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more.

Role Description

BRG is seeking a full-time AI Product & Solutions Engineer to drive firm-wide adoption of secure and governed AI by combining product ownership and practice discovery with hands-on engineering and production delivery. This role partners directly with practice leaders and experts to identify high-value opportunities, define success metrics, and deliver scalable AI-enabled solutions, especially those involving LLMs, RAG pipelines, and agentic workflows, built primarily on Azure.

The role also serves as a key liaison across BRG’s expert communities, internal IT teams, and vendors to ensure solutions are secure, compliant, operationally supportable, and cost-effective, with clear documentation and measurable business impact.

Role Balance (Target Allocation)

  • ~50% Product/Discovery/Adoption:
    • discovery sessions
    • roadmap & prioritization
    • stakeholder alignment
    • training
    • change management
    • adoption metrics
  • ~50% Engineering/Delivery/Operations:
    • design/build/test/deploy LLM solutions
    • RAG/agents
    • integrations
    • monitoring
    • evaluation
    • reliability
    • Tier III troubleshooting

Primary Duties & Responsibilities

  • A) Product Ownership, Practice Discovery & Consulting (≈ 50%)
    • 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.
  • B) Engineering, Architecture & Production Delivery (≈ 50%)
    • Design and ship production AI capabilities such as RAG, prompt/tool patterns, and agentic 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.
  • C) Governance, Security, Compliance & Cost Discipline (Embedded Across)
    • Ensure solutions comply with BRG security, privacy, and regulatory requirements; implement governance patterns (RBAC/Entra ID, Key Vault/secrets, content safety/guardrails, private networking where needed).
    • Create and maintain architecture and integration documentation that supports auditability, reuse, and long-term support.
    • Monitor utilization and optimize cost/performance (model choice, throughput strategy, search tier sizing) with reporting on value delivered.
  • D) Cross-Functional Delivery & Vendor / SaaS Enablement
    • Manage end-to-end efforts for onboarding/integrating AI-related SaaS or services (requirements, vendor selection, implementation, integration, training, ongoing support).
    • Collaborate with internal IT, business partners, and vendors while managing multiple initiatives and maintaining strong customer relationships.

Qualifications

  • Required
    • 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

Minimum Knowledge, Skills & Abilities

  • Product: discovery facilitation, roadmap ownership, prioritization, adoption planning, and outcome measurement.
  • Engineering: Python-based solution delivery and integration patterns; ability to ship supportable production features.
  • AI/LLM: RAG pipelines, chunking/embedding strategies, agent workflows, and evaluation/quality approaches.
  • Cloud: strong Azure foundation plus cost management and architecture tradeoffs.
  • Security/Governance: least privilege access, secrets handling, privacy/PII discipline, and guardrails/responsible use.
  • Operations: documentation/runbooks, troubleshooting/root cause analysis, automation, and Tier III support mindset.

Salary Range

$130,000-$190,000

Candidate must be able to submit verification of his/her legal right to work in the U.S., without company sponsorship.

#LI-REMOTE

Company Description

BRG combines world-leading academic credentials with world-tested business expertise purpose-built for agility and connectivity, which sets us apart—and gets you ahead.

At BRG, our top-tier professionals include specialist consultants, industry experts, renowned academics, and leading-edge data scientists. Together, they bring a diversity of proven real-world experience to economics, disputes, and investigations; corporate finance; and performance improvement services that address the most complex challenges for organizations across the globe.

Our unique structure nurtures the interdisciplinary relationships that give us the edge, laying the groundwork for more informed insights and more original, incisive thinking from diverse perspectives that, when paired with our global reach and resources, make us uniquely capable to address our clients’ challenges. We get results because we know how to apply our thinking to your world.

At BRG, we don’t just show you what’s possible. We’re built to help you make it happen.

BRG is proud to be an Equal Opportunity Employer. Our hiring practices provide equal opportunity for employment without regard to race, religion, color, sex, gender, national origin, age, United States military veteran status, ancestry, sexual orientation, marital status, family structure, medical condition including genetic characteristics or information, veteran status, or mental or physical disability so long as the essential functions of the job can be performed with or without reasonable accommodation, or any other protected category under federal, state, or local law.

Job Requirements

  • Required 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
  • Minimum Knowledge, Skills & Abilities
  • Product: discovery facilitation, roadmap ownership, prioritization, adoption planning, and outcome measurement.
  • Engineering: Python-based solution delivery and integration patterns; ability to ship supportable production features.
  • AI/LLM: RAG pipelines, chunking/embedding strategies, agent workflows, and evaluation/quality approaches.
  • Cloud: strong Azure foundation plus cost management and architecture tradeoffs.
  • Security/Governance: least privilege access, secrets handling, privacy/PII discipline, and guardrails/responsible use.
  • Operations: documentation/runbooks, troubleshooting/root cause analysis, automation, and Tier III support mindset.
  • Salary Range
  • $130,000-$190,000
  • Candidate must be able to submit verification of his/her legal right to work in the U.S., without company sponsorship.
  • #LI-REMOTE

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