Senior AI Engineer | US | Remote

About This Opportunity

We are representing a confidential observability platform company seeking a Senior AI Engineer to join their remote team in the United States. Our client is a globally distributed organization operating across 40+ countries, backed by tier-one venture capital, and serving thousands of enterprise customers.

This is a high-impact role where you'll own the technical direction for AI agent infrastructure and automation systems that power marketing operations, revenue operations, and business development teams. You'll build production multi-agent architectures, LLM integrations, and backend services that eliminate manual work and drive measurable operational efficiency.

Responsibilities

Agentic Systems & AI Infrastructure:

• Own end-to-end development of multi-agent AI systems from architecture through deployment and ongoing operations
• Build modular, composable agentic systems using orchestration frameworks such as LangChain, CrewAI, Anthropic MCP, or similar technologies
• Develop reusable agentic skills that operate across multiple interfaces including Slack, dashboards, internal applications, and CLIs
• Implement comprehensive observability including logging, performance metrics, prompt iteration, model evaluation, and cost management
• Establish governance standards for AI workflows including access controls, audit trails, PII handling, and human-in-the-loop escalation

Systems Integration & Backend Services:

• Build MCP servers, APIs, CLIs, and microservices connecting AI models to business systems including BigQuery, Slack, CRMs, email platforms, and analytics tools
• Architect data flows for retrieval-augmented generation (RAG), connecting LLMs to knowledge bases, customer data, and real-time business context
• Build serverless or containerized services using GCP Cloud Functions and Cloud Run that scale with usage

Automation & Workflow Enablement:

• Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to scope high-impact automation problems with measurable business outcomes
• Design and deploy workflows using orchestration tools such as n8n, Workato, or custom platforms with CI/CD and production reliability standards
• Build self-service systems with documentation, playbooks, and enablement materials that empower partner teams to operate independently

What We're Looking For

Required Experience:

• 8+ years of software engineering experience with depth in backend development, systems integration, or data/analytics engineering
• 2+ years hands-on experience applying LLMs and AI to production workflows, not just prototypes
• Strong proficiency in Python and JavaScript/Node.js with Git-based workflows, code review practices, and testing discipline
• Hands-on experience with LLM frameworks and patterns including prompt engineering, RAG, function calling/tool use, structured output parsing, and evaluation
• Experience building and operating multi-agent systems at scale including agent decomposition, orchestration patterns, state management, and production monitoring
• Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services
• Understanding of LLM failure modes and production mitigations including confidence thresholds, fallback logic, human escalation, and cost/latency management
• Proven ability to identify high-leverage problems, push back on low-impact requests, and deliver end-to-end with minimal direction
• Fluency with AI-assisted development tools such as GitHub Copilot, Cursor, or Claude Code
• Clear technical communication skills for both engineers and business stakeholders

Bonus Qualifications:

• Experience with vector databases or retrieval pipelines (Pinecone, Weaviate, ChromaDB, Qdrant, pgvector)
• Familiarity with marketing or sales platforms such as Salesforce, Customer.io, HubSpot, Marketo, or Outreach
• Experience with frontend frameworks including React or Slack Block Kit for building user-facing AI tool interfaces
• Observability tooling for AI systems such as LangSmith, Weights & Biases, or custom evaluation frameworks
• Experience with workflow orchestration platforms (n8n, Temporal, Prefect, Airflow)
• Familiarity with Model Context Protocol (MCP) or similar standards
• Prior work automating marketing, sales, or customer success workflows in a B2B SaaS environment
• Active participation in open-source communities

How We Work With You

When you apply through Get A Job.ai, our recruiting team will review your background and conduct an initial screening to understand your experience with AI engineering, multi-agent systems, and backend development. If there's a strong match, we'll submit your profile to our client for consideration.

We coordinate all communication with the client on your behalf throughout the interview process. Please do not contact the client directly, as this may affect your candidacy.

Pay

Pay via Get A Job.ai: USD $154,445 - $185,334 base compensation, plus equity (RSUs) and benefits. Actual compensation will be determined based on your level, experience, and skillset as assessed during the interview process.

Get A Job.ai is an equal opportunity employer. We welcome applications from candidates of all backgrounds and are committed to building an inclusive recruiting process.