Sobre este puesto de Full Stack Engineer en Thinkahead
We’re hiring a full stack engineer who is comfortable across all parts of the stack (Python, JavaScript, React/Vue, APIs, AI/LLM integration) and can help ship production-grade UI using established designs and component libraries. You must be able to own and deliver full end-to-end features across the stack.
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 while meeting business timelines.
- 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
Must have
- 7+ years of software engineering experience, with significant time in Python building production services.
- 2+ years hands-on with an agentic coding harness — Cursor, Windsurf/Devin, or Claude Code — used as a daily driver on production work, not occasional or trial use.
- Ready to hit the ground running with agentic development: a solid, practical command of agent skills, rules, prompt engineering, and loop engineering, and the judgment to know when each applies.
- 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).
Nice to have
Preferred Certfications
Preferred, not required. We hire based on demonstrated ability. A certification on its own is never a substitute for hands-on experience.
- AWS Certified AI Practitioner (AIF-C01)
- AWS Agentic AI Demonstrated
- AWS Certified Generative AI Developer – Professional (AIP-C01)
- Anthropic Academy developer path
- Also valued: AWS Certified Machine Learning Engineer – Associate (MLA-C02), Claude Certified Architect – Foundations , and GitHub Copilot GH-300.
What Success Looks Like
- 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.