AI Solutions Analyst
$100k - $120kPublic Consulting Group
Public Consulting Group LLC (PCG) is a leading public sector solutions implementation and operations improvement firm that partners with health, education, and human services agencies to improve lives. Founded in 1986, PCG employs approximately 2,000 professionals throughout the U.S.-all committed to delivering solutions that change lives for the better. The firm is a member of a family of companies with experience in all 50 states, and clients in three Canadian provinces and Europe. PCG offers clients a multidisciplinary approach to meet challenges, pursue opportunities, and serve constituents across the public sector. To learn more, visit
PCG is seeking an AI Solutions Analyst to support the design, delivery, and ongoing monitoring of AI-enabled solutions within state government environments. This role bridges client-facing requirements work with hands-on responsibility for how the AI system actually performs - translating policy and program needs into structured requirements, and using evaluation data to diagnose and improve system output quality. The ideal candidate combines business analysis discipline with practical, hands-on fluency in enterprise AI - not just understanding how agentic workflows behave, but analyzing evaluation results with basic statistical reasoning and using that diagnosis to shape system behavior, within real-world constraints of performance, cost, and explainability. This role is ideal for candidates who want to work inside how enterprise AI environments by writing the requirements, measuring the results, and closing the gap between the two. What This Role Is Not- Not a data science or ML infrastructure role (no model architecture, training pipelines, or platform engineering)
- Not a traditional business analyst role focused only on documentation
- Not a project manager role only owning delivery execution or sprint ceremonies
- Not a prompt-only or AI tool usage role without enterprise context understanding
- Not a role where success is measured by prompt-writing volume - tuning here is diagnosis-led, grounded in evaluation data, not trial-and-error prompting
Client Engagement & Requirements Facilitation
- Support and lead client requirements sessions and discovery discussions
- Translate policy and operational workflows into structured requirements
- Serve as a bridge between stakeholders and technical teams
- Support design of AI-enabled solutions and define use cases
- Develop and document AI workflows
- Design evaluation test sets with attention to sample size and representativeness across case types (LTC, ADB, etc.)
- Analyze evaluation results using basic statistical reasoning - error rates, false positive/negative patterns, distribution of failure modes - to identify where and why the system underperforms
- Iterate on prompts and instructions to address root causes identified through evaluation analysis
- Identify tradeoffs related to performance, cost, token usage, and explainability
- Partner with technical leads on tuning cycles within established review and sign-off processes
- Support broader program operations as needed - process design, cross-workstream coordination, and other work that helps scale delivery beyond a single engagement
- Strong communication skills
- Bachelor's degree from an accredited institution
- 4+ years of experience as a Business Analyst, Solutions Analyst, or Consultant
- Experience translating complex needs into structured deliverables
- Client-facing experience in requirements sessions and workshops
- Working knowledge of basic statistics - sample sizes, error rates, false positive/negative distinction, and comfort reading distributions - sufficient to design representative evaluation test sets and interpret results
- Hands-on experience iterating on prompts/instructions for LLM-based systems in a production or near-production setting
- Working knowledge of AI systems, including behavior, limitations, and agentic workflows
- Practical understanding of model selection tradeoffs, context/cost constraints, and agentic workflow limitations beyond prompt-level interaction with frontier models
- Technical understanding of system architecture, data flows, APIs, and integrations
- Experience supporting public-sector or compliance-driven programs
- Familiarity with AI implementation patterns such as RAG and multi-agent workflows
- Exposure to cloud platforms (AWS Bedrock preferred, Azure acceptable)
- Familiarity with AI risks: bias, hallucination, explainability
- Familiarity with compliance-driven delivery environments, including responsible AI practices, federal or state regulatory requirements, or structured governance frameworks
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