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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting AI agents and building secure infrastructure for SaaS integrations, with a strong focus on production-readiness and compliance. Proficient in optimizing internal AI platforms and collaborating across teams to enhance operational efficiency.
Highest-signal resume keywords
Backend Engineering ExperienceMCP Server DevelopmentKubernetes DeploymentREST API UnderstandingData Engineering Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Agent FrameworksOAuth 2.0Credential ManagementGoogle Cloud AuthenticationDatabricksData Ingestion PipelinesLogging StandardsSecurity PracticesPerformance OptimizationAutomation of Processes
Soft Skills
Strong Communication SkillsAdaptabilityCuriosity About AI ToolsAbility to Navigate Competing Priorities
Tools & Technologies
MCP ServersClaudeCowork PluginsAI Operations ToolsService Accounts
Industry Keywords
SaaS IntegrationsProduction-Grade SystemsCompliance MonitoringAI Platform SecurityData Warehouses
Tech Stack
Tools & technologiesCloudKubernetes
About the role
Key responsibilities & impact- Architect AI agents that execute reliable multi-step workflows using reasoning, tool calls, and decision-making
- Design, build, and deploy MCP servers for external SaaS integrations and Placer.ai internal tools
- Build secure OAuth and credential-management infrastructure for connector authentication
- Define and apply production-readiness standards for MCP servers, including security, Kubernetes deployment, logging, and access controls
- Triage connector requests and bug reports and distinguish rollout-critical work from backlog
- Build and maintain Cowork plugins and Claude skills for Marketing, Operations, Data, and other workflows
- Automate manual and repetitive processes using Claude
- Own and improve Placer.ai’s internal Databricks BI environment, including data restructuring and ingestion pipelines
- Build tooling to track internal AI usage, adoption, and high-value use cases
- Optimize compute, storage, networking, performance, and cost across the internal AI platform
- Implement AI platform security practices including identity management, encryption, and compliance monitoring
- Partner across AI Operations, R&D, Data Science, GTM, and other teams
- Report to the COO and own the path from integration request to production-grade system
- Help establish triage and review processes enabling safe self-service across the organization
Requirements
What you’ll need- 8+ years of backend engineering experience
- Prior experience with MCP servers, LLM tool use, or AI agent frameworks
- Prior experience in data engineering or analytics tooling
- Solid understanding of REST APIs, OAuth 2.0, and credential management
- Experience with Google Cloud authentication patterns, including gcloud and service accounts
- Experience building and deploying services to Kubernetes or equivalent container infrastructure
- Familiarity with Databricks or similar data warehouses/data lakes is a plus
- Comfort working without an existing playbook and adapting as role definition, standards, and tooling evolve
- Strong communication skills for translating business requests into engineering requirements
- Ability to navigate competing priorities across R&D Architecture, AI Enablement, and business teams
- Demonstrated use of AI tools and curiosity about applying them in new ways
- Comfort integrating generative AI into day-to-day workflows
- No educational credential explicitly required
Benefits
Comp & perks- Competitive salary
- Excellent benefits
- Fully remote
- Medical coverage
- Dental coverage
- Vision coverage
- Flexible time off
- 401K
- Equity awards for certain roles
- Opportunity to work with and learn from top-notch talent
- Central and critical role at Placer.ai