Fullstack Developer (Only w2)

As a Software Engineer, AI Platform - Contract, you’ll help build and improve internal platform capabilities that enable teams to use AI services safely, reliably, and at scale. This role blends full-stack product development with platform engineering: building user experiences, backend APIs and services, cloud integrations, observability workflows, and AI provider integrations across AWS and emerging Google Cloud Platform initiatives.

You’ll work hands-on with engineers and platform partners to deliver practical tooling for API access, model and provider integration, usage visibility, governance workflows, and secure developer onboarding. The ideal candidate is a strong mid-level engineer who is comfortable moving across frontend, backend, and cloud/platform concerns in an evolving technical space.

Responsibilities

· Build and maintain full-stack platform features across user-facing workflows, backend APIs, and supporting services.

· Develop clean, reliable services using TypeScript, Node.js, Python and modern API patterns.

· Contribute to user experiences using React ecosystem tools and modern frontend practices.

· Integrate with AI providers and platform services, including model APIs, embeddings, streaming responses, and provider abstraction patterns.

· Support cloud-native delivery on AWS, with growing collaboration around Google Cloud Platform-based initiatives.

· Help implement secure API access, authorization, rate limits, routing, usage tracking, and observability workflows.

· Work with product, platform, security, and DevOps partners to turn ambiguous requirements into practical implementation plans.

· Write maintainable code, tests, documentation, and operational notes that help the platform scale beyond initial pilots.

Required Qualifications

· 7+ years of professional software engineering experience.

· Hands-on experience building production applications with TypeScript, JavaScript, Node.js, React or similar frontend frameworks, HTML, and CSS.

· Experience building or integrating backend services, REST APIs, and service-to-service workflows.

· Working knowledge of AWS services and cloud-native deployment patterns.

· Experience with databases and caching systems such as PostgreSQL, DynamoDB, Redis, or similar technologies.

· Familiarity with Docker, CI/CD, Git, automated testing, and modern software delivery practices.

· Ability to work across frontend, backend, and platform concerns in an ambiguous, evolving product area.

· Interest in AI/GenAI systems, API platforms, governance, observability, and secure enterprise software.

AI, Platform, and Cloud Experience

· Experience integrating with AI providers such as AWS Bedrock, OpenAI, Anthropic, Azure OpenAI, Google Gemini, or similar services.

· Familiarity with model APIs, embeddings, streaming responses, prompt/response handling, or AI application patterns.

· Understanding of API gateway and platform concepts such as authentication, quotas, rate limits, routing, policy enforcement, developer onboarding, and usage tracking.

· Experience with observability tooling, logs, traces, metrics, audit events, or cost and usage reporting.

· Exposure to AWS platform services such as Lambda, ECS, EKS, API Gateway, S3, CloudWatch, Secrets Manager, RDS, DynamoDB, or related services.

· Exposure to Google Cloud Platform services such as Cloud Run, GKE, IAM, networking, Apigee X, or API management is valuable.

Preferred Qualifications

· Experience building Python services or tooling with FastAPI, Pydantic, async/httpx, pytest, or modern packaging workflows.

· Experience using Python with AI provider SDKs, embeddings/vector workflows, agent frameworks, or model evaluation tooling.

· Experience with Apigee X or other enterprise API gateway platforms.

· Experience with Kubernetes, EKS, GKE, or container orchestration in production environments.

· Experience with platform engineering, internal developer platforms, SDKs, API products, or shared service platforms.

· Familiarity with OpenAI-compatible APIs, LangChain, agent frameworks, AI evaluation, prompt workflows, or guardrail concepts.

· Experience with Go, Erlang, or Elixir.

· Experience in retail, e-commerce, high-transaction systems, or enterprise integration environments.

· Comfort working with security, privacy, governance, and compliance-oriented requirements.