Summary
Lead cloud and AI solution architecture, advise clients, build production-grade machine learning systems, mentor engineers, and deliver scalable cloud-native platforms.
Highlights
Remote work with flexible hours, certification support, career growth, advanced AI projects, and leadership opportunities.
Description
What You’ll Do:
Design and build cloud-native data, LLM-based, and agentic AI solutions addressing real client business challenges Implement and optimize RAG systems for production use cases Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor.
Support presales: discovery calls, technical proposals, scoping, and client-facing demos Own the technical direction of client engagements from discovery through delivery — the go-to authority for clients and the internal team Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools.
Deploy ML and LLM-based solutions Implement MLOps, LLMOps, and AgentOps practices: CI/CD, automated testing, model monitoring, and experiment tracking.
Lead architecture reviews, produce technical design documents, and contribute to standards Mentor engineers, lead code reviews, and share knowledge across the team.
What You’ll Bring:
Mindset
Full-stack mindset, comfortable across AI, backend development, and cloud infrastructureAlready using AI tools in your daily workflow (Claude Code, Copilot, or similar)Proactive and self-directed; you own outcomes end-to-end and spot problems before they're handed to youB2+ English, comfortable collaborating across distributed, multicultural teams
Presales & Client Engagement
Owns the client technical relationship; leading discovery, decomposing ambiguous requirements into technical components, presenting architecture, and pushing back on scope when it doesn't match timeline or budgetProduces scoped, phased delivery plans with clear deliverables, dependencies, and risksExperience with cost estimation and cloud architecture cost optimization
AI & Python/ Data & Cloud
7+ years building and running production systems — not only demos and POCsHands-on experience building production LLM-based applications and agentic workflowsExperience in integrating AI/ML components into solutionsExperience with LLM APIs (OpenAI, Anthropic, or AWS Bedrock)Experience building and optimizing RAG systemsUnderstanding of LLM evaluation techniques and quality assurance approachesExperience deploying and maintaining AI/ML models in production environmentsPython skills: OOP, design patterns, clean architecture, and performance optimizationExperience building RESTful APIs with FastAPI, Django REST, or FlaskExperience in making and defending architectural trade-off decisionsExperience with Docker and KubernetesHands-on experience with AWS (Bedrock AgentCore, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP consideredUnderstanding of CI/CD practices applied to ML and AI pipelinesFamiliarity with model monitoring, observability, and drift detection
Nice to Have
AWS and Claude Code CertificationsCI/CD pipeline experience (GitHub Actions, GitLab CI)Experience in an additional language (Go, Node.js, or Rust)Hands-on experience with Apache Spark, Apache Airflow, Kafkа
What We Offer:
Opportunity to work with cutting-edge AI and cloud solutionsInternal training programs (Leadership, Public Speaking, and more) with full support for AWS and other professional certificationsCareer growth: a clear path toward SA or beyond; we actively develop our engineersAccess to the latest AI tools and premium subscriptionsLong-term B2B collaborationRemote with flexible hoursPrivate medical insurance or a budget for your medical needsPaid sick leave, vacation, and public holidaysEquipment and all the tech you need for comfortable, productive work
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.