BayOne Solutions

Title: AI Solutions Architect
— MVP Development Team
Location:
Remote (PST); preference for San Francisco, Los Angeles, or Seattle metro, with occasional travel to the local hub
Engagement:
6+ month Contract
Pay Range:
$90-100/hr on W2C/C2C
Domain:
Enterprise SaaS for the public sector — financials, HR payroll, procurement, and workforce management for government agencies
About the Role
We're building a net-new MVP that demonstrates full enterprise ERP-style capability for government and public sector organizations. We need an AI Solutions Architect to make AI a core part of that product from day one, not a later add-on.
You'll be the AI counterpart to the Product Manager and Engineering Manager. With Product, you'll shape which AI features earn a place in the MVP; with Engineering, you'll design how they're built into the platform, so AI capabilities are working and demonstrable at the MVP demo milestone.
This role is AI-native in how it works, not only in what it builds. You'll use LLMs, AI frameworks, MCP, and AI coding assistants every day to design, prototype, and ship faster, and you'll help the wider team work the same way.
What You'll Do
<ul>
<li>Partner with the Product Manager to identify and prioritize AI use cases across financials, HR payroll, procurement, and workforce management (e.g. document processing for invoices and requisitions, conversational assistants for HR and finance users, anomaly detection in spend and payroll, forecasting).</li>
<li>Partner with the Engineering Manager to define the AI architecture — model selection, retrieval (RAG), agentic workflows, MCP-based tool and data integration, and connection to the core platform — as part of the overall MVP technical plan.</li>
<li>Use LLMs, AI coding assistants (e.g. Claude Code, GitHub Copilot, Cursor), and agentic tools in your own day-to-day work to prototype, design, document, and review faster.</li>
<li>Set up and champion AI-assisted workflows for the development team — coding assistants, MCP servers that connect tools and data, and agents for testing, documentation, and code review — to accelerate delivery to the MVP demo.</li>
<li>Build rapid proofs of concept to validate AI feature bets before full engineering investment.</li>
<li>Guide the development team (local and offshore distributed) in building, testing, and shipping AI features, including design and code reviews.</li>
<li>Select AI ML models, tooling, and services that fit the chosen cloud-native stack, balancing capability, cost, and time to MVP.</li>
<li>Define evaluation methods for AI accuracy, latency, and cost, and make sure AI features are reliable enough for a live demo.</li>
<li>Design for public sector requirements from the start: data privacy, security, auditability, explainability, and responsible AI.</li>
<li>Help define what MVP-complete means for AI features and drive them to the demo milestone.</li>
<li>Represent AI in occasional in-person planning or demo sessions at the preferred coastal hub.</li>
</ul>
What You Bring
<ul>
<li>8+ years in software engineering or solutions architecture, including 3+ years designing and shipping AI ML solutions in production.</li>
<li>Hands-on experience taking LLM-based features (RAG, agents, copilots, document AI) from concept to production in a SaaS product.</li>
<li>Daily, hands-on use of LLMs and AI developer tools (e.g. Claude Code, GitHub Copilot, Cursor) in your own work, with concrete examples of how they sped up delivery.</li>
<li>Working knowledge of Model Context Protocol (MCP): building or configuring MCP servers to connect models with tools, APIs, and data.</li>
<li>Strong knowledge of major model providers (e.g. Anthropic Claude, OpenAI, Gemini, open-source models) and AI frameworks (e.g. LangChain, LangGraph, LlamaIndex, Claude Agent SDK, OpenAI Agents SDK).</li>
<li>Experience with cloud AI services (AWS Bedrock, Azure AI Foundry, or Vertex AI).</li>
<li>Experience in enterprise SaaS, ideally ERP, GovTech, HR HCM, procurement, or financial software.</li>
<li>Proficiency in Python, plus experience integrating AI services into modern backend frontend frameworks through APIs and microservices.</li>
<li>Experience on an MVP 0-to-1 product, including scope and technical debt trade-offs under a deadline.</li>
<li>Comfort working with distributed and or offshore engineering teams.</li>
<li>Based anywhere in the continental US but able to work core hours in Pacific Time.</li>
<li>Strong preference for candidates based in or near San Francisco, Los Angeles, or Seattle, with willingness to travel occasionally to that location for in-person work.</li>
</ul>
Nice to Have
<ul>
<li>Background in public sector, civic tech, or compliance-heavy enterprise software.</li>
<li>Familiarity with AI governance and public sector compliance considerations (e.g. NIST AI RMF, FedRAMP StateRAMP, CJIS).</li>
<li>Experience with AWS AI services (Bedrock, SageMaker, Textract).</li>
<li>Experience with multi-agent orchestration and LLM evaluation observability tools (e.g. LangSmith, Arize).</li>
<li>Experience fine-tuning or deploying smaller models for cost-sensitive workloads.</li>
</ul>

AI Solutions Architect (MVP Development Team)

AI Solutions Architect (MVP Development Team)

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