Engineering Manager, Platform

Jobtailor

San Francisco (CA)

On-site

USD 180,000 - 260,000

Full time

4 days ago

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Job summary

Jobtailor in San Francisco seeks an experienced backend engineering leader to guide a team of platform and backend engineers. You will own execution across Platform projects, set priorities, and drive design through production with ongoing reviews and mentorship.

You will collaborate with the Head of Engineering on platform strategy, architecture, hiring, and priorities, balancing speed, reliability, and cost while raising the team’s technical bar.

Qualifications

7+ years of professional software engineering experience.
Previous experience directly managing a software engineering team.
Strong hands-on backend engineering experience and willingness to continue writing production code.
Deep experience designing and operating distributed backend systems.
Strong system design and software architecture skills.
Experience building production systems on AWS or another major cloud platform.
Experience owning production systems with meaningful scale, reliability, and availability requirements.
Strong understanding of databases, APIs, asynchronous systems, queues, caching, and distributed architectures.
Experience with infrastructure, observability, deployment systems, and production operations.
Demonstrated ability to lead complex technical projects from ambiguity through production.
Ability to effectively manage both senior and junior engineers.
Strong communication skills and ability to work across engineering, product, ML, and business teams.
Experience with Python and modern backend frameworks.
Experience with AWS services such as Lambda, ECS/EKS, SQS, RDS, DynamoDB, S3, CloudWatch, or related technologies.
Experience operating event-driven or asynchronous distributed systems.
Experience building systems with strict latency and reliability requirements.
Experience with containers, infrastructure-as-code, and modern CI/CD systems.
Experience building data infrastructure or large-scale processing pipelines.
Experience supporting ML systems, model inference, LLM applications, or AI infrastructure.
Experience in healthcare technology or other regulated environments.
Experience with HIPAA-compliant systems and healthcare data.
Experience working in fast-moving startup environments where engineering leaders remain deeply involved in execution.
Legally authorized to work in the US
Must answer whether visa sponsorship or transfer will be required.

Responsibilities

Lead, manage, and develop a team of platform and backend engineers.
Own execution and delivery across Platform projects.
Set priorities, break down ambiguous projects, and move projects from design through production.
Run technical planning, design reviews, and engineering reviews.
Coach senior and junior engineers and raise the team’s technical bar.
Partner with the Head of Engineering on platform strategy, architecture, hiring, and organizational priorities.
Identify and resolve execution risks.
Design and build production backend and platform systems.
Take ownership of technically difficult or high-priority projects.
Review architecture, code, infrastructure changes, and technical designs.

Skills

Backend Engineering

Team Management

AWS Cloud Services

System Design

Distributed Systems

Python

Backend Frameworks

Databases

APIs

Asynchronous Systems

Infrastructure-as-Code

CI/CD Systems

Data Processing Pipelines

Model Inference

Event-Driven Systems

HIPAA Compliance

Healthcare Technology

Tools

AWS Lambda

ECS/EKS

SQS

RDS

DynamoDB

CloudWatch

Job description

Lead, manage, and develop a team of platform and backend engineers
Own execution and delivery across Platform projects
Set priorities, break down ambiguous projects, and move projects from design through production
Run technical planning, design reviews, and engineering reviews
Coach senior and junior engineers and raise the team’s technical bar
Partner with the Head of Engineering on platform strategy, architecture, hiring, and organizational priorities
Identify and resolve execution risks
Design and build production backend and platform systems
Take ownership of technically difficult or high-priority projects
Review architecture, code, infrastructure changes, and technical designs
Debug complex production and distributed-system issues
Make architectural decisions balancing speed, reliability, scalability, and maintainability
Establish reusable technical patterns and standards
Own backend platform reliability, scalability, and performance
Design systems supporting growing clinical workloads
Improve observability, monitoring, alerting, and incident response
Own cloud infrastructure and improve security, cost efficiency, and operational resilience
Build shared services and infrastructure for product engineers
Improve developer experience, deployment workflows, testing, and engineering productivity
Eliminate technical bottlenecks
Partner with ML engineers and researchers to productionize AI capabilities
Build infrastructure for model inference, evaluation, experimentation, and data processing
Support applied ML initiatives and scalable foundations for the ML organization
Balance AI quality with latency, reliability, scalability, and cost
Report directly to the Head of Engineering

Requirements

7+ years of professional software engineering experience
Previous experience directly managing a software engineering team
Strong hands-on backend engineering experience and willingness to continue writing production code
Deep experience designing and operating distributed backend systems
Strong system design and software architecture skills
Experience building production systems on AWS or another major cloud platform
Experience owning production systems with meaningful scale, reliability, and availability requirements
Strong understanding of databases, APIs, asynchronous systems, queues, caching, and distributed architectures
Experience with infrastructure, observability, deployment systems, and production operations
Demonstrated ability to lead complex technical projects from ambiguity through production
Ability to effectively manage both senior and junior engineers
Strong communication skills and ability to work across engineering, product, ML, and business teams
Experience with Python and modern backend frameworks
Experience with AWS services such as Lambda, ECS/EKS, SQS, RDS, DynamoDB, S3, CloudWatch, or related technologies
Experience operating event-driven or asynchronous distributed systems
Experience building systems with strict latency and reliability requirements
Experience with containers, infrastructure-as-code, and modern CI/CD systems
Experience building data infrastructure or large-scale processing pipelines
Experience supporting ML systems, model inference, LLM applications, or AI infrastructure
Experience in healthcare technology or other regulated environments
Experience with HIPAA-compliant systems and healthcare data
Experience working in fast-moving startup environments where engineering leaders remain deeply involved in execution
Legally authorized to work in the US
Must answer whether visa sponsorship or transfer will be required

Core Competencies

Demonstrates extensive experience in backend engineering, team leadership, and system design, with a strong focus on building scalable and reliable production systems. Proficient in managing complex technical projects and collaborating across engineering, product, and ML teams.

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