Full time Remote
Our client is a multimodal AI company with deep expertise in building state-of-the-art foundation models. By unifying genomics, imaging, text, and audio, they deliver holistic, human-centric insights that help organizations transform data into actionable intelligence. Their approach puts people at the core, driving breakthroughs across sectors where understanding human behavior and biology is critical.
Responsibilities
As an Engineering Manager, you’ll lead a cross-functional team of engineers working on mission-critical projects while maintaining your technical edge through hands-on involvement in architectural decisions and code reviews. You’ll balance strategic leadership with practical engineering knowledge, scaling both the team and technical systems as the company grows.
1. Team Leadership & Development
- Build, manage, and mentor a high-performing engineering team of 6–10 engineers
- Create career growth paths for team members through regular 1:1s, performance reviews, and development plans
- Foster a culture of technical excellence, continuous learning, and psychological safety
- Participate in hiring and employer branding to attract and retain top engineering talent
- Manage team workload, capacity planning, and sprint allocations across multiple projects
2. Technical Guidance & Execution
- Contribute to architectural decisions and maintain technical oversight across projects
- Participate in code reviews to ensure code quality, maintainability, and alignment with best practices
- Stay hands-on with JavaScript and Python codebases, diving into code when necessary to unblock the team
- Guide the team through technical challenges, making informed trade-offs between technical debt and delivery
- Collaborate with senior engineers to implement scalable, maintainable systems and processes
3. Product & Business Alignment
- Partner with product managers to translate business requirements into technical specifications
- Work with stakeholders across the organization to align engineering priorities with company goals
- Balance short-term deliverables with long-term technical investments and platform evolution
- Provide realistic timelines and set appropriate expectations for engineering deliverables
- Communicate technical concepts and constraints effectively to non-technical stakeholders
4. Process & Operations
- Refine and optimize engineering processes as the team scales
- Implement effective agile methodologies tailored to the team’s needs and company phase
- Establish metrics and KPIs to measure engineering productivity and system performance
- Manage technical debt and make strategic decisions about when to address it
- Lead incident response and post-mortems to improve system reliability and team learning
Requirements
- 7–10 years of professional software engineering experience
- 3+ years of engineering management experience, preferably in a startup environment
- Hands-on coding experience with JavaScript (React, Node.js) and Python
- Experience scaling engineering teams and systems through different company growth stages
- Strong understanding of the software development lifecycle, from ideation to production and maintenance
- Proven track record of delivering complex software projects on time and within scope
- Experience implementing and refining agile development processes
- Excellent communication skills with both technical and non-technical stakeholders
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
Preferred Qualifications
- Experience at both early-stage and growth-stage startups
- Familiarity with infrastructure as code, cloud services (AWS/GCP/Azure), and CI/CD pipelines
- Experience with microservices architecture and distributed systems
- Knowledge of data engineering, machine learning, or AI systems
- Contributions to open-source projects or technical community
- Experience with product-led growth or B2B SaaS companies
- MBA or technical leadership training
Technical Skills
- Languages: JavaScript (React, Node.js), Python, TypeScript
- Infrastructure: AWS/GCP, Docker, Kubernetes, Terraform
- Databases: SQL, NoSQL (MongoDB, DynamoDB), data warehousing
- Practices: CI/CD, test automation, agile methodologies
- Monitoring & Observability: Datadog, New Relic, Prometheus, etc.
