AI Developer (Centralized Operating System / Enterprise Intelligence)

About the role

We are seeking a hands-on, highly pragmatic AI Developer to architect, build, and continuously refine our core enterprise AI operating system ("Alfred"). In this role, you will not just write prompts or integrate basic chatbots—you will build a connected intelligence layer across the entire business. You will construct pipelines that allow AI to ingest and reason over real-time operational metrics, vendor APIs, Google Chat conversations, emails, CRM data, and internal documentation. This role is ideal for a builder-first software engineer who views AI as a foundational technology layer, possesses strong systems-thinking capabilities, and excels at turning high-level business needs into reliable production code.

What you'll do

• Centralized AI Operating System Development ("Alfred"):
• Architect, build, and deploy a unified AI operating system connecting Sales, Marketing, Operations, Procurement, and Communications.
• Build secure infrastructure for multi-agent workflows, contextual retrieval, and cross-departmental intelligence sharing.
• Translate broad business and operational needs into automated, AI-driven workflows.
• LLM Engineering & Knowledge Retrieval:
• Implement Retrieval-Augmented Generation (RAG) architectures to process both structured (databases, sales metrics) and unstructured (emails, Google Chat logs, docs) data.
• Design robust prompt engineering, context window management, and orchestration strategies for production LLM systems.
• Establish evaluation frameworks to ensure high output precision, reliability, and cost-efficient API/model usage.
• API Integration & Data Pipelines:
• Build and maintain integrations with Google Workspace (Gmail, Google Chat APIs), POS platforms, vending management systems, and third-party vendor APIs (including manufacturer/hardware endpoints).
• Design ETL pipelines to keep the central AI context continuously updated without manual intervention.
• Develop webhooks, RESTful endpoints, and automated data synchronization between disparate internal dashboards.
• Operations & Workflow Automation:
• Identify manual operational bottlenecks (e.g., dispatching field technicians, updating CRM records, tracking stock anomalies) and replace them with automated AI workflows.
• Build decision-support tools that allow team members and leadership to query company context in natural language and receive real-time answers.
• Security, Governance & Monitoring:
• Implement role-based access control (RBAC), authentication, and authorization so AI agents only access data appropriate for specific workflows.
• Monitor performance, API latency, error rates, and system output accuracy; debug integration failures swiftly.
• Document technical architecture, pipeline designs, and API contracts.

Requirements

• Experience: 2–5 years of professional experience in AI development, software engineering, or automation engineering.
• Core Development Skills: Strong backend programming fundamentals using Python or JavaScript / TypeScript.
• AI & LLM Proficiency: Hands-on experience building applications powered by LLM APIs (OpenAI, Anthropic, Gemini, etc.), agent frameworks, and context orchestration.
• Systems Integration: Proven track record of integrating REST APIs, webhooks, and complex third-party platforms (specifically Google Workspace / Google Cloud APIs).
• Data Management: Solid understanding of relational/SQL databases, data pipelines, and structuring unstructured data for semantic search.
• Working Hours: Ability to regularly overlap with US Pacific Standard Time (9:00 AM – 5:00 PM PST) for team collaboration, reviews, and operational alignment.
• Mindset: A pragmatic builder who avoids unnecessary complexity, takes ownership of end-to-end deliverables, and works comfortably with ambiguous requirements.

About Somehere

We recruit, vet, and place top 1% remote talent for up to 80% less than US equivalents.

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