Mid-Level AI Infrastructure Engineer [$259k/yr+] TS/SCI-FS Poly
SYSTOLIC, INC.
Jessup, United States of America
3 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Intermediate Compensation
$ 259KJob location
Jessup, United States of America
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Cloud Engineering
Encodings
Continuous Integration
DevOps
Distributed Systems
Python
Performance Tuning
Prometheus
Systems Integration
Web Applications
AI Infrastructure
Data Logging
High Performance Computing
System Availability
Large Language Models
Grafana
AI Platforms
Kubernetes
Infrastructure Automation Frameworks
Virtual Agents
BIG-IP Access Policy Manager (APM)
Job description
- Design, implement, and optimize scalable AI infrastructure for model inference, production AI services, and applications, including retrieval augmented generation (RAG) and autonomous agents.
- Implement observability solutions with OpenTelemetry, Grafana, and Prometheus.
- Automate infrastructure provisioning and configuration using DevOps and CI/CD.
- Ensure high availability, reliability, and performance of AI platform components, contributing to system security.
- Provide technical guidance.
- Requires strong Python, AWS, Kubernetes, and experience with vLLM, LiteLLM, Agentic AI, LangChain, vector databases, high-performance computing, and web application architecture., * Join us in building the next generation of AI infrastructure that will power innovation across the customer organization. We're seeking a full-stack software engineer to support our AI infrastructure team. In this role, you'll help build and maintain the platform that provides the foundation for the customer's AI capabilities, focusing on inference services while supporting the broader ecosystem of AI-enabled applications.
- This role is intended for experienced engineers who can independently design, implement, and operate scalable AI infrastructure components.
- Responsibilities: Design, implement, and optimize infrastructure for AI model inference at scale.
- Support the development and maintenance of production AI services and applications, including retrieval augmented generation (RAG), autonomous agents, and emerging technologies.
- Navigate ambiguity and define solutions for underspecified systems and requirements.
- Drive adoption of new technologies and practices across engineering teams.
- Implement monitoring, logging, and observability solutions for AI services.
- Automate infrastructure provisioning and configuration using IaC principles.
- Ensure high availability, reliability, and performance of AI platform components.
- Contribute to security best practices for AI systems and data.
- Provide technical guidance and informal mentorship to junior engineers.
Requirements
- Degree: Technical bachelor's degree or equivalent experience
- Years of experience: 8+ years
- Total Compensation: $259k+ yearly, * Skills Requirements: Proven experience building and maintaining production systems at scale.
- Experience with high-volume web application architecture and performance optimization.
- Strong background in systems integration across diverse technologies and platforms.
- Hands-on experience with cloud engineering in AWS.
- Proficiency with Kubernetes administration and deployment patterns.
- Strong Python programming skills.
- Experience implementing observability solutions (APM, OpenTelemetry, Grafana, Prometheus).
- Familiarity with CI/CD pipelines and DevOps practices.
- Strong change management and organizational influence skills.
- Ability to thrive in ambiguous environments and create structure where needed.
- Excellent communication and collaboration skills.
- Nice to Haves: Experience with AI inference serving technologies (vLLM, LiteLLM, etc.).
- Previous experience with agentic frameworks (LangChain).
- Knowledge of vector databases and embedding systems.
- Experience with high-performance computing or distributed systems.