AI Infrastructure Engineer
Content + Source + Freshness • 12 Dec 2025 • 95% confidence
Offer value
A compelling opportunity with high impact in AI infrastructure at a Series A startup, promising to shape foundational backend systems.
- High-demand role in AI infrastructure at a Series A startup
- Opportunity to shape foundational backend systems
- Collaborative, dynamic work environment
- Requires strong backend engineering skills (Python)
Pros
- Joining a growing company with significant potential
- Possibility to influence the development of core backend systems
- Collaborative work environment with cross-functional teams
Cons
- Early-stage startup may entail more uncertainty
- Demanding requirements for technical proficiency and experience
- Limited structure compared to more established organizations
Who it's for
Mid to Senior • On-site
Good fit
- Mid-level backend engineers
- Candidates eager to influence foundational systems
- Tech professionals interested in startups
Not recommended for
- New graduates or inexperienced developers
- Individuals seeking only stable, corporate environments
- Those resistant to rapid changes and innovation
Motivation fit
Key skills
About the job
About the Role
We’re hiring an AI Infrastructure Engineer to shape and scale the backend systems that power our AI platform. As a Series A company, your work will be foundational, enabling safe, efficient, and reliable AI workflows from end to end.
What You’ll Do
-
Design and implement scalable backend architectures for AI workloads (inference, orchestration, monitoring).
-
Own distributed job orchestration with Temporal and related systems.
-
Improve data pipeline performance by designing smarter caching strategies (e.g., file deduplication, hot/cold storage, Redis caching layers) to reduce redundant compute and API calls.
-
Build observability, monitoring, retries, and fault tolerance into all workflows.
-
Manage infrastructure reliability, incident response, and performance.
-
Develop tooling and platform infrastructure to support rapid growth.
-
Partner with ML engineers to bring models to production at scale.
What We’re Looking For
-
4+ years of backend engineering (Python is a must).
-
Strong background in distributed systems, job orchestration, and task queues.
-
Deep knowledge of concurrency, parallelism, and multithreading—including async/await, event loops, thread pools, synchronization primitives, deadlocks, and race conditions—is a must. You should know how to design systems that maximize throughput without sacrificing correctness or safety.
-
Hands-on experience with Temporal, Redis, Airflow, Celery, RabbitMQ (or similar).
-
Experience with LLM serving and routing fundamentals (rate limiting, streaming, load balancing, budgets).
-
Comfortable with containers & orchestration: Docker, Kubernetes.
-
Familiarity with cloud platforms (AWS/GCP) and IaC (Terraform).
-
Experience with multiple storage systems: S3, Postgres, MongoDB, Redis, and Elasticsearch.
-
Track record scaling systems in startups or fast-paced environments.
-
Understanding of deploying, monitoring, and optimizing AI/ML systems in production with strong CI/CD practices.
Why You’ll Love Working Here
-
Play a foundational role at a fast-growing Series A startup that is shaping the future of AI in enterprise workflows.
-
Collaborate across Product, ML, and Platform teams, being the bridge between AI logic and scalable execution.
-
Build infrastructure that enables real value for large enterprises: low-code, secure, and scalable AI workflows.
-
Join a company that’s scaling thoughtfully and values developer experience.
