Senior Software Engineer, Inference Platform
Skills
About the role
About Aion
Aion is the enterprise AI platform, a full-stack solution for building, fine-tuning, and deploying AI at scale. Whether an organization is modernizing internal operations, launching AI-powered products, or transforming customer experiences, Aion takes them from concept to production on a single, unified platform.
We work differently than most AI companies: our teams deploy alongside our customers, turning production-ready AI into real business outcomes in weeks, not quarters.
We're a fast-growing, VC-backed startup led by founders with a track record of successful exits. With teams across the US, UK, and India, we're building the next generation of enterprise AI and we're looking for exceptional people to help us scale.
Who You Are
You're a seasoned engineer who has built and scaled high-performance inference systems for AI/ML workloads. . You understand the complexities of serving models at scale latency optimization, resource orchestration, autoscaling dynamics, and production reliability. You've designed distributed systems that handle thousands of requests per second while maintaining sub-second response times and cost efficiency.
Experience with Golang is strongly preferred, and exposure to inference engines (vLLM, TGI, TensorRT), containerization, and distributed systems is an added bonus. You take ownership of platform-level decisions, think strategically about performance vs. cost trade-offs, and want your work to power AI inference for thousands of developers globally.
You're product-minded, you understand how your technical decisions impact developers using aion's platform and think about the end-to-end user experience. You're a team player comfortable wearing multiple hats one day you're optimizing inference latency, the next you're joining customer calls to understand their deployment challenges, and the day after you're helping with UI/UX, customer success, documentation and product ops.
What You'll Do
Inference Platform Architecture & Core Services
Design and build aion's inference service platform the backbone for serving AI models at scale across diverse workloads
Own and architect core platform components: AI Gateway, Resource Orchestrator, Runtime Engines, and Autoscaler
Design highly modular, scalable, and extensible low-level designs (LLDs) for inference infrastructure components
Lead high-level design discussions, establish architectural patterns, and drive technical decision-making for the inference stack
Model Deployment & Lifecycle Management
Understand and optimize the dynamics of model deployment, version upgrades, and rollback strategies
Build robust deployment pipelines for seamless model updates with zero-downtime deployments
Implement strategies for efficient GPU utilization and model cold-start optimization
Performance & Distributed Systems
Implement highly performant and optimized software for low-latency, high-throughput inference serving
Build and debug production-grade code in distributed systems handling real-time AI workloads
Optimize inference pipelines for latency, throughput, batching efficiency, and resource utilization
Design fault-tolerant systems with graceful degradation and automatic recovery mechanisms
Observability & Engineering Excellence
Build high-performance telemetry and observability stack for inference metrics, performance tracking, and debugging
Implement comprehensive monitoring for model latency, throughput, error rates, GPU utilization, and cost per inference
Conduct thorough code reviews to maintain code quality, performance standards, and architectural consistency
Establish engineering best practices for testing, documentation, and production readiness.
Requirements
Technical Skills & Experience
4+ years of experience building and scaling backend systems, distributed platforms, or inference infrastructure
Strong understanding of AI/ML inference systems and experience with inference engines (vLLM, TGI, TensorRT-LLM, or similar)
Deep knowledge of distributed systems design, microservices architecture, and API gateway patterns
Proficiency in Golang strongly preferred; Python, Rust, C++ for performance-critical components a plus
Experience with container orchestration (Kubernetes, Docker) and infrastructure-as-code
Solid understanding of autoscaling strategies, load balancing, and resource scheduling algorithms
Experience building high-throughput, low-latency systems with sub-100ms response time requirements
Familiarity with message queues (Kafka, RabbitMQ), databases (PostgreSQL, Redis), and event-driven architectures
Knowledge of GPU computing, model serving optimizations (batching, quantization, multi-tenancy), and resource allocation
Experience with observability tools (Prometheus, Grafana, OpenTelemetry) and distributed tracing
Understanding of API design, rate limiting, authentication/authorization, and security best practices
Exposure to AI model deployment workflows and model lifecycle management is highly desirable
Bonus/ Good to Have
HPC & Cluster Management: Experience handling large-scale HPC clusters using Kubernetes and Slurm for job scheduling, resource allocation, and workload orchestration
Data Engineering: Expertise with data pipelines, ETL systems, and large-scale data processing frameworks
Systems-Level Programming: Experience with low-level systems programming such as storage systems, Kubernetes operators, OS-level software development, or daemon services (llm-d, system agents)
ML Platform Engineering: Experience productionizing ML pipelines, batch job orchestration, model fine-tuning workflows, and Jupyter notebook orchestration systems
Enterprise Deployment: Experience platformizing and packaging software for on-premises deployments or customer VPC installatiaons with emphasis on security, compliance, and operational simplicity
Benefits
Preferred Attributes:
High ownership, self driven and biased for action
Strong strategic thinking and ability to connect technical decisions to business impact
Excellent communication and mentoring skills
Thrives in ambiguity, fast-paced environments, and early-stage startup culture
Why Join aion?
Work directly with high-pedigree founders shaping technical and product strategy
Build infrastructure powering the future of AI computers globally
Significant ownership and impact with equity reflective of your contributions
Competitive compensation, flexible work options, and wellness benefits
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