Role Overview
- Team Leadership: Lead, coach, and develop engineers. Own performance management, hiring, onboarding, career development, accountability, and team culture.
- Metrics & Delivery: Manage engineering KPIs, productivity, capacity, resource allocation, quality, and delivery commitments across multiple projects. Use data to improve performance and outcomes.
- Engineering Operations: Own development tooling, cloud environments, CI/CD, testing, deployment, security, and engineering logistics. Optimize AI-assisted development workflows, infrastructure costs, and operational efficiency.
- Customer Engagement: Work directly with US and other clients to understand requirements, guide technical solutions, manage delivery expectations, and ensure measurable business outcomes within Chiri's AI MSP model.
- Hands-On Engineering: Contribute to architecture, coding, integrations, code reviews, troubleshooting, and production support. Partner with the CTO on technical standards and implementation.
- Proven people leadership, including direct management, coaching, performance management, and developing high-performing engineering teams in a remote environment.
- Experience managing engineering metrics, delivery operations, resource allocation, and multiple concurrent initiatives.
- Strong customer-facing communication skills, including working with business and technical stakeholders.
- Significant hands-on full-stack engineering background with TypeScript and Python, including backend services, APIs, integrations, and modern frontend frameworks such as React and Next.js.
- Production experience with AWS and/or Azure, Docker, Terraform or similar infrastructure-as-code tools, Git, CI/CD, SQL, and automated testing.
- Experience building or operating AI-powered applications involving LLMs, agents, or automation workflows.
- Strong understanding of software architecture, security, reliability, and production operations.
- Excellent English communication skills and the ability to lead effectively in a remote environment.
- Engineering leadership experience in an MSP, consulting, professional services, or forward-deployed engineering environment.
- Experience with AI-native development tools, autonomous coding agents, and engineering productivity analytics.
- Experience with SaaS platforms, enterprise integrations, and managing ongoing security requirements like SOC2.
- Experience scaling engineering teams in startup or high-growth environments, bonus points for experience in working with Latin America teams.
Our SCOUT Values
Skills Required
- Direct people management, coaching, performance management, and development of high-performing engineering teams in a remote environment
- Experience managing engineering metrics, delivery operations, resource allocation, and multiple concurrent initiatives
- Strong customer-facing communication with business and technical stakeholders
- Significant hands-on full-stack engineering experience with TypeScript and Python
- Experience with backend services, APIs, integrations, React, and Next.js
- Production experience with AWS and/or Azure, Docker, Terraform or similar infrastructure-as-code tools, Git, CI/CD, SQL, and automated testing
- Experience building or operating AI-powered applications involving LLMs, agents, or automation workflows
- Strong understanding of software architecture, security, reliability, and production operations
- Excellent English communication skills and ability to lead effectively in a remote environment
- Engineering leadership experience in an MSP, consulting, professional services, or forward-deployed engineering environment
- Experience with AI-native development tools, autonomous coding agents, and engineering productivity analytics
- Experience with SaaS platforms, enterprise integrations, and ongoing security requirements such as SOC 2
- Experience scaling engineering teams in startup or high-growth environments, including work with Latin America teams
What We Do
We turn business problems into governed applications, agents, and targeted software. Our forward-deployed pods combine senior operators and engineers. Each pod embeds with client teams, learns how work happens, and ships production systems within weeks. Chiri supports AI adoption, AI optimization, and AI software engineering. We assess workflows, design operating models, and deploy digital workers into existing tools. We also audit scattered AI systems, add governance, consolidate systems, and measure return on investment. Chiri Brain provides the shared foundation for every deployment. Its ontology preserves company knowledge and operating context. Sherpa connects current applications and provides broad AI model access. Glacier applies security, permissions, validation, and audit controls. Client data remains client-owned. Each Statement of Work defines the custom deliverables and related terms. Chiri supports work across go-to-market, engineering, finance, and people operations. Our systems work inside tools such as Slack, HubSpot, Gmail, Teams, Salesforce, Jira, and Zendesk. We build from a first production application through enterprise scale. Chiri Brain remains after the pod steps back. This model gives companies lasting AI capability without requiring a separate internal AI company.
Why Work With Us
We value curiosity, ownership, speed, and people who love solving complex problems with simple solutions. If you’re excited about building a meaningful company, working with highly talented people, and making a real impact from day one, we’d love to meet you.
