Software Engineer II – AI InfrastructureJoin us in building the next generation of AI infrastructure that will power innovation across critical mission environments.We are seeking an experienced Software Engineer II to support an advanced AI Infrastructure Team responsible for developing and maintaining the platform that serves as the foundation for enterprise AI capabilities. This role focuses on AI inference services while supporting a broader ecosystem of AI-enabled applications, including Retrieval-Augmented Generation (RAG), autonomous agents, and emerging machine learning technologies.The ideal candidate is a highly skilled engineer who can independently design, build, deploy, and operate scalable infrastructure solutions while helping shape the future of AI adoption across mission-critical environments.Key ResponsibilitiesAI Infrastructure & Platform EngineeringDesign, implement, and optimize infrastructure supporting AI model inference at scale.Develop, deploy, and maintain production AI services and applications.Support emerging AI technologies, including:Retrieval-Augmented Generation (RAG)Agentic AI SystemsLarge Language Model (LLM) PlatformsAI Inference ServicesBuild highly available, reliable, and scalable AI platform components.Navigate ambiguous requirements and define practical, scalable technical solutions.Cloud & Systems EngineeringDesign and manage cloud-native infrastructure within AWS environments.Automate infrastructure provisioning and configuration using Infrastructure-as-Code (IaC) principles.Support Kubernetes deployments and administration across production environments.Integrate systems across diverse platforms and technologies.Optimize high-volume web applications and distributed systems for performance and reliability.Observability & OperationsImplement monitoring, logging, and observability solutions across AI services and infrastructure.Develop operational dashboards and alerting capabilities using:GrafanaPrometheusOpenTelemetryApplication Performance Monitoring (APM) toolsSupport incident response, troubleshooting, and root cause analysis efforts.DevOps & AutomationDevelop and maintain CI/CD pipelines.Improve deployment automation and operational efficiency.Promote DevOps best practices across engineering teams.Drive adoption of modern engineering tools and methodologies.Security & CollaborationContribute to secure AI system design and implementation.Support compliance with organizational security requirements.Provide technical guidance and informal mentorship to junior engineers.Collaborate with software engineers, data scientists, platform engineers, and mission stakeholders.Required QualificationsEducation & ExperienceBachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, or a related technical discipline.Substitution:Four (4) additional years of directly related experience may be substituted for a bachelor's degree.ExperienceEight (8) or more years of software engineering experience.Proven experience building and supporting production systems at scale.Experience designing and supporting high-volume web applications.Experience integrating complex systems across multiple technologies and platforms.Experience supporting cloud-native infrastructure in AWS.Experience administering and deploying applications within Kubernetes environments.Technical SkillsStrong Python development skills.AWS Cloud EngineeringKubernetesInfrastructure as Code (IaC)CI/CD PipelinesDevOps MethodologiesMonitoring and Observability PlatformsDistributed Systems ArchitecturePerformance OptimizationSystems IntegrationObservability TechnologiesExperience with one or more of the following:OpenTelemetryGrafanaPrometheusApplication Performance Monitoring (APM) SolutionsProfessional SkillsStrong problem-solving and analytical abilities.Ability to thrive in ambiguous and rapidly evolving environments.Strong organizational influence and change management skills.Excellent written and verbal communication skills.Ability to work independently and collaboratively within highly technical teams.Desired QualificationsCandidates with one or more of the following qualifications are highly desired:Experience with AI inference serving technologies such as:vLLMLiteLLMSimilar inference platformsExperience with agentic AI frameworks such as:LangChainLangGraphSimilar orchestration frameworksExperience with:Vector databasesEmbedding systemsSemantic search technologiesKnowledge of:High-Performance Computing (HPC)Distributed Computing SystemsExperience supporting production AI/ML environments.CompensationSalary Range: $193,000 - $306,000Compensation is based on experience, education, technical expertise, and overall alignment with program requirements.BenefitsMedical CoverageChoose from three comprehensive medical plans through Aetna. The company pays 80% of monthly premiums for employees.Health Savings Account (HSA)Pre-tax contributions for qualified medical expensesCompany contributes 50% of the annual deductible (prorated based on start date)Dental CoverageAetna Passive PPO Max PlanCompany pays 80% of monthly premiumsVision CoverageAetna Vision Preferred Premier 24M PlanCompany pays 80% of monthly premiumsLife Insurance100% Company-Paid Life InsuranceAccidental Death & Dismemberment (AD&D) CoverageShort-Term Disability100% Company-PaidPays 60% of earnings up to $1,500 per week for up to 12 weeksRetirement PlanAutomatic 6% employer contribution to 401(k)Fully vested from day oneEmployee contributions encouraged but not requiredPaid Time Off & Holidays5–6 weeks of PTO depending on tenure11 paid holidays annuallyProfessional Development$5,000 annual tuition reimbursementPaid training, certifications, and industry conferences