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Senior AI & Cloud-Native Software Architect

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Remote

Senior AI & Cloud-Native Software Architect

Jobgether

Senior AI & Cloud-Native Software Architect

Skills

DynamoDBDockerData MiningNodeTypescriptPythonMicroservicesPostgreSQLAWS LambdaDatadogGrafanaAIAWSKubernetesGDPRTerraform

9 days ago

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Important information


Contract type:

Part time

Location:

Brazil

Work mode:

Remote

Published on:

16 October 2026

What they need


This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI & Cloud-Native Software Architect based in Brazil. We are seeking an experienced software architect to lead the design and delivery of secure, scalable, and production-ready AI-enabled applications and cloud-native systems. This hands-on role combines architectural leadership with software engineering, covering generative AI (GenAI), large language models (LLMs), retrieval-augmented generation (RAG), and distributed cloud services. You will translate business needs into robust technical architectures while guiding solutions from discovery and design through implementation and production launch. Working with modern AWS services, event-driven systems, and vector databases, you will help build reliable AI experiences that balance performance, security, scalability, and cost. You will collaborate closely with engineers and stakeholders, establish architectural standards, and promote best practices in testing, observability, and continuous delivery. This remote, part-time contract opportunity is ideal for a technical leader who enjoys solving complex problems while remaining actively involved in building and delivering innovative AI solutions.

Accountabilities

  • Design scalable, secure, and resilient architectures for AI-enabled applications, defining service boundaries, data flows, APIs, and integration patterns.
  • Establish cloud-native architectural approaches across microservices, containerized applications, serverless computing, and event-driven systems.
  • Design, implement, and productionize GenAI and LLM solutions, including model selection and routing, retrieval strategies, evaluation frameworks, AI guardrails, and cost and latency optimization.
  • Architect and develop RAG pipelines using embeddings, vector search, and appropriate data retrieval techniques to deliver relevant, reliable AI-generated responses.
  • Build backend services using TypeScript/Node.js and/or Python, including asynchronous workflows, queues, workers, webhooks, and service integrations.
  • Define non-functional requirements covering reliability, performance, scalability, security, and maintainability, evaluating architectural trade-offs and documenting key decisions through Architecture Decision Records (ADRs).
  • Translate business use cases into technical designs, feasibility assessments, architecture recommendations, and executive-level summaries.
  • Lead architectural decisions throughout the project lifecycle, from initial discovery and solution design to implementation, deployment, and production launch.
  • Guide engineering teams through architecture reviews, code reviews, and technical discussions to ensure consistent standards and maintainable solutions.
  • Design and implement observability practices using appropriate monitoring, logging, tracing, and alerting tools to improve system reliability and operational visibility.
  • Build and maintain secure CI/CD pipelines, automated testing practices, and deployment workflows that support reliable and repeatable software delivery.
  • Apply cloud security best practices across identity and access management, authorization, secrets management, data protection, and secure service-to-service communication.
  • Identify opportunities to improve system architecture, operational efficiency, application resilience, and the overall quality of AI-enabled software.

Requirements

  • At least 7 years of software engineering experience, including significant responsibility for technical design and architectural decision-making.
  • Proven experience owning the architecture of production distributed systems, including microservices, domain-driven design, REST APIs, and asynchronous communication patterns.
  • Hands-on experience delivering production-grade GenAI or LLM applications, including model integration, evaluation, and AI safety controls.
  • Practical knowledge of RAG architectures, embeddings, retrieval strategies, and vector databases such as pgvector, OpenSearch, or equivalent technologies.
  • Strong software engineering skills in TypeScript/Node.js and/or Python, with the ability to design, implement, and maintain production backend services.
  • Deep understanding of cloud-native architecture, including containers, Kubernetes, serverless computing, event-driven messaging, and distributed-system resilience patterns.
  • Strong knowledge of cloud security principles, including identity management, authorization, secrets handling, and data protection.
  • Experience with Docker, CI/CD pipelines, automated testing, and observability platforms or tools such as OpenTelemetry, Grafana, Datadog, or Amazon CloudWatch.
  • Ability to evaluate architectural alternatives, define non-functional requirements, document technical decisions, and communicate trade-offs clearly.
  • Experience guiding engineers through architecture and code reviews and taking ownership of solutions from initial design through production deployment.
  • Strong analytical and problem-solving abilities, with the capacity to translate complex business needs into practical technical solutions.
  • Excellent communication and collaboration skills, including the ability to explain technical concepts and present recommendations to both engineering teams and executive stakeholders.

Nice To Have

  • Experience with AWS services such as Bedrock, Lambda, API Gateway, SQS, EventBridge, Step Functions, ECS/EKS, Aurora PostgreSQL, and DynamoDB.
  • Familiarity with conversational AI and contact center technologies, including WhatsApp Business API, Amazon Connect, Amazon Lex, Twilio, and voice bots.
  • Experience with infrastructure-as-code tools such as Terraform, AWS CloudFormation, or AWS CDK.
  • AWS Certified Solutions Architect – Professional certification or an equivalent cloud architecture qualification.
  • Customer-facing consulting experience, including presenting technical assessments, architecture recommendations, and solution proposals to senior stakeholders.

Benefits

  • Remote work: Work remotely from Brazil, with flexibility in organizing your work within the engagement requirements.
  • Part-time engagement: A part-time opportunity suited to an experienced professional seeking a focused architectural role.
  • Contractor arrangement: Hourly contract engagement, with compensation based on the agreed contractual terms.
  • Immediate start: The role is expected to begin as soon as possible.
  • Technical ownership: Lead architecture decisions and contribute hands-on to the design and delivery of production AI and cloud-native applications.
  • Cutting-edge technologies: Work with generative AI, LLMs, RAG, vector databases, AWS cloud services, and modern distributed architectures.
  • End-to-end impact: Influence solutions from initial discovery and architectural design through implementation, production launch, and ongoing optimization.
  • Technical leadership: Guide engineering teams, establish architectural best practices, and help improve software quality, security, and reliability.
  • Compensation transparency: The position is paid hourly, but a specific rate or range was not provided in the original listing.
  • Additional benefits: Healthcare, paid leave, equipment allowances, and other perks were not specified and should be confirmed during the application process.

How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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