Sr Python Developer with Vue.js

Python Software Engineer with Vue.js12+ Months contractThis is a hybrid role in NYC , NYInterview process: 1st round: 1 hour video interview2nd round: In-person interview in NY officeThe Agent Platform team would like to see candidates with Vue.js + Python experienceSenior Software Engineer, AI Platform Engineering As a Senior Software Engineer, you will focus on the reliability and resilience of mission-critical AI platforms.You will design systems that withstand provider and dependency failures, establish observability and service-level objectives, and keep the platform current as the AI ecosystem evolves.The team’s scope includes Kubernetes-based platform-as-a-service frameworks, model-agnostic AI/LLM gateways, hybrid networking, observability, and self-service developer tooling.We are looking for a collaborative, self-motivated engineer who is comfortable with ambiguity, takes ownership, and enjoys solving complex infrastructure challenges.Legal AI is one of the most exciting and fast-moving areas in technology today.If you are interested in building the foundational platforms that power the next generation of AI products, we'd love to hear from you.What You’ll Do ● 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 across Bloomberg.● 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.What You’ll Bring ● 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 Open Telemetry, 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.