3 дня назад
Principal Software Development Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Principal Software Development Engineer (AI) (Generative AI platforms and intelligent agent systems): Leading the architecture, deployment, and evolution of production-grade AI platforms with an accent on secure MCP servers, containerized workloads, and scalable cloud-native infrastructure. Focus on optimizing inference latency and memory usage, designing enterprise AI standards, and building reliable LLM capabilities with observability and guardrails.
Location: Hybrid in Bangalore, India
Company
develops the cloud-native Zero Trust Exchange platform and cybersecurity solutions powered by security data and AI.
What you will do
- Lead the architecture, deployment, and evolution of large-scale Generative AI platforms and intelligent agent systems in production.
- Build and maintain MCP servers for secure interactions between LLMs, agents, enterprise tools, APIs, databases, and local resources.
- Design and deploy high-performance containerized AI workloads using Docker and Kubernetes.
- Apply model quantization and KV-cache optimization to reduce latency and memory usage.
- Define engineering standards, architectural patterns, and best practices for enterprise AI systems.
- Partner with multidisciplinary teams to deliver secure, observable, and reliable AI capabilities at scale.
Requirements
- 10+ years of software engineering experience with significant expertise in distributed systems, platform engineering, or machine learning infrastructure.
- Proven experience building, deploying, and operating production-grade AI/ML or LLM systems at scale.
- Strong Python skills and experience with systems languages such as Go, C++, Rust, or Java.
- Hands-on experience with Docker, Kubernetes, and cloud-native deployment patterns.
- Foundational understanding of AI/ML technologies and experience leveraging or securing AI-driven solutions.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Nice to have
- Experience implementing AI safety, evaluation benchmarks, guardrails, and LLM observability frameworks.
- Experience with RAG systems, vector databases, embedding pipelines, and retrieval tuning.
- Experience with vLLM, TensorRT-LLM, Triton, Ray Serve, or equivalent inference and serving frameworks.
Culture & Benefits
- Culture centered on customer obsession, collaboration, ownership, accountability, and constructive debate.
- Health plans, vacation and sick time, parental leave, retirement options, and education reimbursement.
- In-office perks and an inclusive environment focused on collaboration and belonging.
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