What you’ll do
Design, build, and maintain backend services in Python, including REST/GraphQL APIs and integrations with internal and external systems.
Implement and integrate AI/LLM-powered workflows (e.g., RAG, agentic workflows, orchestration, prompt/guardrail patterns).
Work across our agentic platform stack to connect services, tools, and data sources into reliable, observable workflows.
Translate UX designs and design systems into clean, maintainable frontend code (React), wiring up APIs, state, and components.
Collaborate with product, UX, and other engineers to break down requirements, estimate work, and deliver in iterative increments.
Write readable, testable code with appropriate unit/integration tests and participate in code reviews.
Help ensure engineering standards, tooling, and CI/CD practices for secure, scalable AI workloads.
Diagnose and resolve issues across the stack (backend, integrations, and frontend behavior).
Use agentic development for rapid quality code and be excited about staying at the forefront of AI skills.
Core skills & experience
4+ years of software engineering experience, with significant time in Python building production services.
Hands-on experience integrating with LLMs or AI services (e.g., AWS Bedrock, OpenAI, Anthropic, LangChain, AgentCore, or similar).
Strong experience with API design and implementation (REST/JSON; GraphQL a plus).
Solid understanding of data modeling, persistence, and integration (SQL/NoSQL, queues, event-driven patterns, etc.).
Working proficiency with modern frontend frameworks (React preferred; Vue/Angular acceptable with willingness to work in React).
Ability to take Figma/wireframes/design specs and implement responsive, accessible UI using a component library / design system (e.g., Tailwind + component kits).
Experience with cloud-native development on at least one major cloud (AWS preferred) and containerization/orchestration concepts.
Familiarity with secure coding practices, authentication/authorization patterns (OAuth/OIDC, RBAC), and observability (logging, metrics, tracing).
Comfortable working in an agile environment with iterative delivery, backlog tracking (e.g., Jira), and collaboration tools.
Experience building or integrating with agentic AI workflows (multi-agent graphs, tools, guardrails, human-in-the-loop flows).
Knowledge of event-driven architectures, message buses, and workflow engines.
Experience with infrastructure-as-code (Terraform, CloudFormation) and CI/CD in cloud environments.
Background working on platform or shared services used by multiple product teams.
Familiarity with design systems and reusable UI component libraries (e.g., shadcn, Material).
Must have
Nice to have
What success looks like in this role
You can own a feature end to end: from API design and AI integration through to a functional UI, without heavy supervision on the frontend.
You move quickly but safely, shipping incremental value while maintaining code quality, reliability, and security.
You collaborate well with product, UX, and other engineers, and you’re comfortable operating in an evolving Enterprise AI platform context.
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