Engineering Team Lead

Brahma

. Lead the Brahma Studio engineering team of 8–10 backend and fullstack engineers .

Posted 9/30/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong leadership in managing engineering teams, with a focus on mentorship, technical decision-making, and maintaining predictable delivery schedules. Proficient in integrating AI-assisted development tools and ensuring code quality through rigorous practices.

Highest-signal resume keywords

Team ManagementTechnical Decision-MakingAI-Assisted Development ToolsServer-Side PythonCI/CD Automation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Server-Side PythonRESTful API DesignMicroservices ArchitectureRelational DatabasesAsynchronous/Caching LayersContainerized EnvironmentsCI/CD AutomationCloud ObservabilityMedia Processing PipelinesAI Model Serving

Soft Skills

Excellent CommunicationStructured MentorshipExpectation Setting

Tools & Technologies

DockerKubernetesDataDogGoogle Cloud Platform

Industry Keywords

Technical RisksCode Quality BenchmarksPredictable Release SchedulesEngineering RigorIterative Technical Deliverables

Tech Stack

Tools & technologies

CloudDockerFFmpegGoogle Cloud PlatformKubernetesMicroservicesPostgresPythonRedis

About the role

Key responsibilities & impact

Lead the Brahma Studio engineering team of 8–10 backend and fullstack engineers
Report directly to the VP of Engineering
Translate product roadmaps and PRDs into clear engineering milestones
Maintain predictable release schedules and establish efficient stand-ups and execution workflows
Identify technical risks, clear blockers, and make pragmatic trade-offs to keep code moving to production
Manage and mentor engineers through 1:1s and structured career development
Partner with the System Architect to shape technical vision and enforce code quality benchmarks
Enforce engineering rigor across code reviews, CI/CD pipelines, and shift-left quality and security practices
Build internal PoCs, demo tools, and custom AI skills
Integrate AI-assisted development tools into daily workflows
Ensure comprehensive logging, monitoring, and alerting using DataDog
Serve as the primary engineering escalation point for Studio engineering
Collaborate with Product Managers, the System Architect, and leadership on platform development commitments
Contribute to technical decisions and write code for less than 20% of the role

Requirements

What you’ll need

3+ years of experience managing engineering teams of 8–10 direct reports
Strong track record of structured mentorship, regular 1:1 cadences, and predictable delivery
Proven ability to break complex platform requirements into iterative technical deliverables and maintain consistent delivery schedules
Strong background in technical decision-making, code reviews, and mentorship
Experience applying AI-assisted development tools and LLM integration workflows
Solid expertise in server-side Python, RESTful API design, microservices architectures, relational databases (PostgreSQL), and asynchronous/caching layers (Redis, background workers)
Practical experience with containerized environments (Docker, Kubernetes), CI/CD automation, and cloud observability platforms
Excellent communication skills, with a track record of setting clear expectations, addressing scope creep early, and communicating technical trade-offs candidly
Understanding of media processing pipelines (FFmpeg, video encoding) or AI model serving (latency, inference) [nice to have]
Exposure to Google Cloud Platform (GCP) or multi-cloud architecture [nice to have]

Benefits

Comp & perks

No benefits, perks, or additional compensation explicitly stated