What are the responsibilities and job description for the Software Engineering – Inference Engineer position at Virtue AI?
About Virtue AI
Virtue AI sets the standard for advanced AI security platforms. Built on decades of foundational and award-winning research in AI security, its AI-native architecture unifies automated red-teaming, real-time multimodal guardrails, and systematic governance for enterprise apps and agents. Deploy in minutes—across any environment—to keep your AI protected and compliant. We are a well-funded, early-stage startup founded by industry veterans, and we're looking for passionate builders to join our core team.
What You’ll Do
As an Inference Engineer, you will own how models are served in production. Your job is to make inferences fast, stable, observable, and cost-efficient—even under unpredictable workloads.
You will:
You understand that inference is a systems problem, not just a model problem. You think in QPS, p99 latency, GPU memory, and failure domains.
Required Qualifications
Virtue AI is an Equal Opportunity Employer. We welcome and celebrate diversity and are committed to creating an inclusive workplace for all employees. Employment decisions are made without regard to race, color, religion, sex, gender identity or expression, sexual orientation, marital status, national origin, ancestry, age, disability, medical condition, veteran status, or any other status protected by law.
We also provide reasonable accommodations for applicants and employees with disabilities or sincerely held religious beliefs, consistent with legal requirements.
Virtue AI sets the standard for advanced AI security platforms. Built on decades of foundational and award-winning research in AI security, its AI-native architecture unifies automated red-teaming, real-time multimodal guardrails, and systematic governance for enterprise apps and agents. Deploy in minutes—across any environment—to keep your AI protected and compliant. We are a well-funded, early-stage startup founded by industry veterans, and we're looking for passionate builders to join our core team.
What You’ll Do
As an Inference Engineer, you will own how models are served in production. Your job is to make inferences fast, stable, observable, and cost-efficient—even under unpredictable workloads.
You will:
- Serve and optimize LLM, embedding, and other ML models' inference across multiple model families
- Design and operate inference APIs with clear contracts, versioning, and backward compatibility
- Build routing and load-balancing logic for inference traffic
- Multi-model routing
- Fallback and degradation strategies
- vLLM or SGLang
- Package inference services into production-ready Docker images
- Implement logging and metrics for inference systems
- Latency, throughput, token counts, GPU utilization
- Prometheus-based metrics
- Analyze server uptime and failure modes
- GPU OOMs, hangs, slowdowns, fragmentation
- Recovery and restart strategies
- Design GPU and model placement strategies
- Model sharding, replication, and batching
- Tradeoffs between latency, cost, and availability
- Work closely with backend, platform (Cloud, DevOps), and ML teams to align inference behavior with product requirements
You understand that inference is a systems problem, not just a model problem. You think in QPS, p99 latency, GPU memory, and failure domains.
Required Qualifications
- Bachelor’s degree or higher in CS, CE, or related field
- Strong experience serving LLMs and embedding models in production
- Hands-on experience designing:
- Inference APIs
- Load balancing and routing logic
- Experience with SGLang, vLLM, TensorRT, or similar inference frameworks
- Strong understanding of GPU behavior
- Memory limits, batching, fragmentation, utilization
- Experience with:
- Docker
- Prometheus metrics
- Structured logging
- Ability to debug and fix real inference failures in production
- Experience with autoscaling inference services
- Familiarity with Kubernetes GPU scheduling
- Experience supporting production systems with real SLAs
- Proven ability to debug and fix inference failures in production
- Comfortable operating in a fast-paced startup environment with high ownership
- Experience with GPU-level optimization
- Memory planning and reuse
- Kernel launch efficiency
- Reducing fragmentation and allocator overhead
- Experience with kernel- or runtime-level optimization
- CUDA kernels, Triton kernels, or custom ops
- Experience with model-level inference optimization
- Quantization (FP8 / INT8 / BF16)
- KV-cache optimization
- Speculative decoding or batching strategies
- Experience pushing inference efficiency boundaries (latency, throughput, or cost)
- Competitive base salary compensation equity commensurate with skills and experience.
- Impact at scale – Help define the category of AI security and partner with Fortune 500 enterprises on their most strategic AI initiatives.
- Work on the frontier – Engage with bleeding-edge AI/ML and deploy AI security solutions for use cases that don't yet exist anywhere else yet.
- Collaborative culture – Join a team of builders, problem-solvers, and innovators who are mission-driven and collaborative.
- Opportunity for growth – Shape not only our customer engagements, but also the processes and culture of an early lean team with plans for scale.
Virtue AI is an Equal Opportunity Employer. We welcome and celebrate diversity and are committed to creating an inclusive workplace for all employees. Employment decisions are made without regard to race, color, religion, sex, gender identity or expression, sexual orientation, marital status, national origin, ancestry, age, disability, medical condition, veteran status, or any other status protected by law.
We also provide reasonable accommodations for applicants and employees with disabilities or sincerely held religious beliefs, consistent with legal requirements.