Senior Full Stack Engineer

Jobgether; Brasil; Remote; BRL 240,000 - 420,000; Full time

Benefits offered by this job

Medical insurance

Paid vacation

Udemy license

Language courses

Internal mobility

Job summary

Jobgether in partnership with a Brazil‑based company seeks a Senior Full Stack Engineer to build production‑ready AI agents and intelligent applications. You will fuse full‑stack development with hands‑on experience in large language models, cloud infrastructure, and AI‑assisted engineering.

Working with a cross‑functional team, you will design secure agent workflows, improve observability and automation, and develop React‑based interfaces and internal tools.

Qualifications

• Demonstrated experience shipping production LLM‑powered features, including prompt design, tool calling, structured outputs, and long‑context workflows, with the ability to explain evaluation strategies, production failures, and corrective actions.

Responsibilities

• Build and maintain production‑grade AI agents using TypeScript, Node.js, AWS Lambda, Step Functions, DynamoDB, Amazon Bedrock, and frameworks such as Strands or LangGraph.
• Design agent workflows by defining what AI models can investigate and which actions must be controlled by deterministic code.
• Develop secure, sandboxed agent runtimes with read‑only access, scoped tools, controlled file access, and appropriate budget and timeout limits.
• Evaluate AI features using benchmark datasets, production replays, calibrated evaluation models, and quality gates based on recall, precision, and false‑positive rates.
• Compare models and inference effort levels before release to ensure reliable, measurable performance.

Skills

TypeScript

Node.js

Python

AWS

Terraform

SQL/NoSQL

CI/CD

English

Tools

LangGraph

Strands

Bedrock

Splunk

VictoriaMetrics

GitLab CI/CD

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Full Stack Engineer based in Brazil.

Join a forward-thinking engineering environment where you will build production-ready AI agents and intelligent applications that solve complex business challenges. In this senior role, you will combine full-stack development expertise with hands‑on experience in large language models, cloud infrastructure, and AI‑assisted engineering. You will design secure, reliable agent workflows, establish rigorous evaluation processes, and ensure AI‑powered features meet high standards for accuracy, performance, and maintainability. Working with a cross‑functional team, you will develop scalable services and internal tools while strengthening observability, automation, and deployment practices. You will also help teams adopt AI development tools effectively and responsibly. This opportunity offers remote flexibility, continuous learning, and the chance to contribute to impactful projects serving international clients.

Accountabilities

• Build and maintain production‑grade AI agents using TypeScript, Node.js, AWS Lambda, Step Functions, DynamoDB, Amazon Bedrock, and frameworks such as Strands or LangGraph.
• Design agent workflows by defining what AI models can investigate and which actions must be controlled by deterministic code.
• Develop secure, sandboxed agent runtimes with read‑only access, scoped tools, controlled file access, and appropriate budget and timeout limits.
• Evaluate AI features using benchmark datasets, production replays, calibrated evaluation models, and quality gates based on recall, precision, and false‑positive rates.
• Compare models and inference effort levels before release to ensure reliable, measurable performance.
• Improve observability through structured logs, reason‑coded metrics, alerts, and production troubleshooting using tools such as Splunk and VictoriaMetrics.
• Maintain Terraform infrastructure across environments while respecting tagging standards, permission boundaries, and security requirements.
• Enhance GitLab CI/CD pipelines for building, testing, deploying, and enforcing quality controls.
• Build resilient integrations that handle retries, rate limits, permanent failures, and outdated application state.
• Use AI coding assistants to accelerate development, review generated code critically, and maintain accurate context for AI‑assisted workflows.
• Review AI‑generated changes for security, correctness, reliability, and maintainability, identifying problems that automated tests may miss.
• Enable engineering teams by configuring assistants, skills, hooks, and MCP servers, while sharing effective practices and supporting colleagues.
• Develop React‑based interfaces and APIs for internal tools, dashboards, and summaries, ensuring outputs are accessible to agents, command‑line interfaces, and Slack.
• Document architecture, workflows, and technical decisions through diagrams, runbooks, and decision records.

Requirements

• Demonstrated experience shipping production LLM‑powered features, including prompt design, tool calling, structured outputs, and long‑context workflows, with the ability to explain evaluation strategies, production failures, and corrective actions.
• Strong TypeScript and Node.js skills, including asynchronous programming, production application development, testing, and monorepo tooling.
• Proficiency in Python for evaluation workflows, data analysis, and scripting.
• Hands‑on experience with AWS serverless technologies, particularly Lambda, Step Functions, DynamoDB, IAM, event‑driven architectures, and Amazon Bedrock.
• Experience safely reviewing and modifying Terraform infrastructure across multiple environments.
• Practical SQL and NoSQL database experience, including schema changes and migrations in live systems.
• Strong observability and debugging skills, including designing metrics, logs, and alerts for non‑deterministic AI systems.
• Proficiency in CI/CD practices; experience with GitLab CI/CD is preferred.
• Regular use of AI‑assisted development tools, with the ability to validate generated code and assess its quality.
• Fluent spoken and written English, with strong communication skills and the ability to explain technical trade‑offs, collaborate across teams, and encourage adoption of effective engineering practices.

The Following Qualifications Are Desirable

• Experience with multi‑agent architectures, MCP servers, or LLM evaluation frameworks such as Strands Evals.
• Knowledge of LLM cost optimization techniques, including model routing, prompt caching, and token budgets.
• Understanding of prompt‑injection defenses and AI agent security.
• Experience with React and GraphQL for internal applications and developer tools.
• Familiarity with Java and Spring Boot for integrating with existing services.
• Experience with code intelligence, retrieval systems, indexing, symbol search, or knowledge bundles.
• Knowledge of Kubernetes, AWS AppSync, and EventBridge.
• Experience with Playwright or Cucumber for automated testing.
• Anthropic Claude Certified Developer or Architect certification.

Benefits

• Fully remote work: Work remotely from Brazil with flexibility in your working environment.
• Health and well‑being: Company‑paid medical insurance, mental health programs, and five additional sick‑leave days per year without documentation requirements.
• Paid time off: 20 working days of paid vacation annually, in addition to local bank holidays.
• Professional development: Access internal meetups, conferences, workshops, a Udemy license, language courses, and company‑paid certifications.
• Career growth: Learn from a global community of experienced professionals and expand your technical expertise.
• Internal mobility: Access opportunities to change projects when appropriate to support your professional development and career goals.
• Long‑term employment: Join a stable, ongoing professional environment with opportunities to grow.
• International projects: Contribute to large‑scale engineering initiatives for international and fast‑growing clients.
• Collaborative culture: Work in a welcoming environment that encourages knowledge sharing, open communication, teamwork, and regular team‑building activities.
• Modern technology: Work with emerging AI technologies and engineering practices to develop solutions with meaningful real‑world impact.