Senior Software Engineer, AI Platform Engineering
Contract
RESPONSIBILITIES
● Improve platform reliability and resilience by designing for failure, defining and meeting SLOs, leading incident response, and reducing operational toil.
● Design, build, and operate Kubernetes-based PaaS frameworks, AI/LLM gateways, APIs, and self-service tools for AI applications.
● Develop model-agnostic gateway capabilities for providers such as OpenAI, Anthropic, Gemini, and AWS Bedrock, including routing, fallback, retries, rate limiting, and cost controls.
● Build observability systems covering metrics, logs, traces, dashboards, and alerting to detect and resolve issues before they affect clients.
● Develop networking solutions that connect applications across public-cloud and on-premises environments.
● Provision and manage cloud infrastructure using Terraform and modern software engineering practices.
● Keep platforms secure and current through dependency patching, runtime upgrades, migrations, and provider-integration updates.
● Create frameworks, templates, and workflows that improve developer productivity and reduce operational overhead.
● Evaluate emerging AI technologies and adapt the platform to support new development patterns and use cases.
QUALIFICATIONS
● 6+ years of professional software engineering experience.
● Strong Python skills and experience developing production-grade backend services and APIs; Java experience is a plus.
● Experience designing and operating distributed systems in public-cloud environments, with a strong understanding of failure modes and resilient design patterns.
● Hands-on AWS experience, including services such as EC2, S3, IAM, and container-based workloads.
● Experience with Infrastructure as Code, preferably Terraform.
● Experience with production operations, including metrics, logging, tracing, alerting, SLOs, and incident response.
● Strong knowledge of software architecture, databases, networking, cloud infrastructure, and modern application development.
● A degree in computer science, engineering, or a related field, or equivalent practical experience.
Preferred Qualifications
● Experience building or operating API gateways, LLM gateways, or similar proxy layers with routing, fallback, rate limiting, caching, and cost tracking.
● Experience with OpenTelemetry, Prometheus, Grafana, Datadog, or similar observability tools.
● Experience with Kubernetes and autoscaling technologies, preferably Amazon EKS and Karpenter.
● Knowledge of AWS networking and security, including VPC, Direct Connect, IAM, and cloud security controls.
● Experience with chaos engineering, load and failure testing, capacity planning, or disaster recovery.
● Experience developing AI-powered applications, agent-based systems, model-inference services, or AI serving platforms.
● Familiarity with AI development tools such as Claude Code, Cursor, or GitHub Copilot.
● Working knowledge of machine learning concepts and the ML development lifecycle. Experience with SageMaker, Bedrock, PyTorch, TensorFlow, or scikit-learn is a plus.
● The ability to learn quickly and independently lead large technical initiatives from concept through production.