BRG Concepts is seeking a full-time AI Product & Solutions Engineer to drive firm-wide adoption of secure and governed AI. This role involves combining product ownership and hands-on engineering to deliver scalable AI-enabled solutions while partnering with practice leaders to identify high-value opportunities.
Responsibilities:
- 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 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
- 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
- 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
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
- 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
- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Certified: Azure Solutions Architect Expert
- AWS AI Practitioner
- AWS Solutions Architect