Sr. Software Engineer (AI Systems & Infrastructure)

Description: We are seeking a highly experienced and driven Sr. Software Engineer to join our full stack LLM integration and delivery team. The ideal candidate will have a strong background in building scalable AI-powered applications and the infrastructure that supports them, with a focus on delivering exceptional user experiences. You will play a crucial role in architecting and developing the systems that power our cutting-edge LLM applications, ensuring they perform reliably at enterprise scale while enabling rapid iteration and deployment.

Responsibilities:

• Lead the design and development of scalable LLM-powered applications and services.
• Architect infrastructure solutions that support rapid iteration and deployment of AI features
• Collaborate directly with product teams to translate user needs into technical solutions.
• Build and maintain the platforms that enable your team to ship AI features quickly and reliably.
• Develop and manage automation tools to improve system reliability and development efficiency.
• Implement and maintain monitoring, alerting, and logging systems.
• Conduct capacity planning and performance tuning for AI workloads.
• Lead and participate in incident response and post-mortem analyses.
• Mentor junior team members and contribute to the overall growth of the engineering team.
• Continuously identify and implement improvements to our systems and development processes.

Skills Requirements:

• SWE with AI experience LLM,RAG and MCP
• Active and current TS.SCI w FSP
• 12+ years of experience in software engineering with focus on scalable systems.
• Strong full-stack development experience with user-facing applications.
• Strong programming skills in languages such as Python, Go, or Java.
• Extensive experience with cloud platforms (e.g., AWS, GCP, Azure) and their services.
• Proficiency in containerization technologies (Docker, Kubernetes).
• Experience with infrastructure-as-code tools (e.g., Terraform, Ansible, Puppet).
• Expertise in monitoring and observability tools (e.g., Prometheus, Grafana, ELK stack).
• Familiarity with CI/CD pipelines and practices.
• Strong problem-solving skills and ability to troubleshoot complex systems.
• Excellent communication skills and ability to work in a collaborative environment.
• Experience building products that prioritize user experience and product-market fit.

Nice to Haves:

• Experience working with Large Language Models (LLMs) and related infrastructure.
• Experience with AI/ML model serving and optimization.
• Background in product-focused engineering environments.
• Familiarity with machine learning operations (MLOps) practices.
• Experience with A/B testing and feature flagging for AI features.
• Contributions to open-source projects.
• Experience with distributed systems and microservices architectures.
• Knowledge of security best practices and compliance requirements.
• Experience with real-time data processing and streaming platforms (e.g., Apache Kafka, Apache Flink).
• Familiarity with chaos engineering principles and tools.