Software Engineering Manager
Role details
Job location
Tech stack
Job description
As a Software Engineering Manager at VIDA, you will have a strong technical depth in cloud-native, distributed data processing systems - high-throughout, horizontally scalable architectures capable of processing millions to billions of events, managing fan-out/fan-in workflows, and orchestrating large-scale data movement across distributed compute clusters. In this role, you will manage and grow a team of backend and platform engineers responsible for building VIDA's distributed compute and data backbone: high-volume ingestion pipelines, scalable workflow engines, secure data storage layers, and AI/ML-supporting infrastructure for the VIDA Intelligence Platform and VIDA Biobank. You'll partner closely with Product, Data Science, QA, Security, and Operations to deliver highly reliable, compliant, multi-tenant systems that support pharma trials, large-scale imaging research, and next-generation AI workloads.
As a Software Engineering Manager, your key responsibilities will be:
Team Leadership & Delivery
- Lead, mentor, and develop a team of software engineers focused on backend services, distributed systems, and cloud infrastructure.
- Build and engineering culture grounded in reliability, observability, automation, and high accountability.
- Drive execution of critical platform initiatives: scalable DICOM ingestion, distributed workflow orchestration, batch data processing pipelines, and date lake/lakehouse systems.
- Ensure Engineering best practices across code quality, testing, CI/CD, IaC, and operational readiness.
Technical Ownership & Architecture
- Provide strong hands-on technical guidance in system design, distributed systems patterns, and cloud-native architecture.
- Own the reliability and performance of distributed components such as:
- Event-driven pipelines (Kinesis, Kafka, Pub/Sub equivalents)
- Workflow orchestration (Step Functions, Temporal, Airflow)
- Scalable microservices for multi-tenant data access
- Collaborate with senior architects and the VP of Engineering on platform roadmaps and architectural evolution.
- Champion modern distributed systems practices including idempotent operations, partitioning, caching, backpressure management, and autoscaling.
Cross-Functional Collaboration
- Work with Product Management to break down features into clear technical plans and deliverable increments.
- Partner with Data Science/ML teams to support model training, inference workflows, and large-scale compute jobs.
- Coordinate with Security, Compliance, and DevOps to ensure systems meet HIPAA, SOC2, GDPR, and GxP standards.
- Collaborate with Customer Success and Support teams to diagnose issues and improve platform-level SLAs., All VIDA employees are expected to be flexible and have an entrepreneurial mindset. Other duties may be assigned as needed. In addition, VIDA offers a wide selection of benefits including health insurance (medical, dental, vision), retirement planning (401k), and paid time off to name a few.
Requirements
Do you have experience in Team management?, * 7+ years of experience building large-scale backend or distributed systems; 2+ years managing or leading technical teams.
- Deep experience with cloud-native distributed architectures (AWS preferred).
- Hands-on knowledge of:
- Event-driven systems (Kafka/Kinesis/PubSub)
- Microservices at scale (ECS/EKS/Lambda)
- Distributed data storage (S3, RDS, DynamoDB, Delta Lake)
- Workflow orchestration frameworks
- LLM Coding tools (Claude Code, OpenAI Codex, or Gemini Antigravity
- Strong design and distributed systems fundamentals: consensus, partitioning, caching, backpressure, idempotency, retries, stream processing.
- Proficient in modern programming languages (Python, Go, Java, or similar).
- Experience building or managing multi-tenant SaaS systems with strict SLAs.
- Experience operating systems in compliance-sensitive environments (healthcare, finance, enterprise SaaS).
- Strong experience with aligning teams to adopt AI assisted programming methodologies
Preferred Qualifications
- Experience with medical imaging, DICOM, or AI/ML data processing.
- Familiarity with lakehouse architectures, Databricks, large-scale batch compute platforms.
Benefits & conditions
Pulled from the full job description
- 401(k)
- Health insurance
- Paid time off
- Vision insurance
- Dental insurance