Techlead / Solutions Architect (Python & Genai, Aws)

What You’ll Do:Write clean, production-grade Python across AI integrations, backend services, and RESTful APIsImplement and optimize RAG systems for production use casesDesign and build LLM-based and agentic AI solutions that address real client business challengesOwn the technical direction of client engagements from discovery through deliverySupport presales: discovery calls, technical proposals, scoping, and client-facing demosLead architecture reviews, produce technical design documents, and contribute to standards across the Python practiceMentor engineers, lead code reviews, and share knowledge across the teamBuild and maintain strong relationships with key client stakeholders as a trusted technical advisorWhat You’ll Bring:MindsetFull-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 teamsPresales & Client EngagementOwns 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 optimizationPython, AI & Cloud7+ years building and running production systems not only demos and POCsStrong understanding of AI/ML concepts and experience integrating AI/ML components into solutionsStrong Python proficiency: OOP, design patterns, clean architecture, and performance optimizationExperience building RESTful APIs with FastAPI, Django REST, or FlaskExperience making and defending architectural trade-off decisions: microservices vs monolith, sync vs event-driven, SQL vs NoSQLStrong testing practices: pytest, mocking, and integration tests for AI systemsExperience with Docker and KubernetesHands-on experience building production LLM-based applications and agentic workflowsExperience 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 environmentsHands-on experience with AWS (SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP consideredExperience with React/VueAWS and Claude Code CertificationsNice to HaveExperience with Streamlit or Gradio for AI prototypingModern Python tooling (ruff, uv, pyproject.toml, pyright)CI/CD pipeline experience (GitHub Actions, GitLab CI)Experience in an additional language (Go, Node.js, or Rust)Front-end experienceWhat 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 workWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.

Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure Already 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 you B2+ 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 budget Produces scoped, phased delivery plans with clear deliverables, dependencies, and risks Experience with cost estimation and cloud architecture cost optimization Python, AI & Cloud 7+ years building and running production systems not only demos and POCs Strong understanding of AI/ML concepts and experience integrating AI/ML components into solutions Strong Python proficiency: OOP, design patterns, clean architecture, and performance optimization Experience building RESTful APIs with FastAPI, Django REST, or Flask Experience making and defending architectural trade-off decisions: microservices vs monolith, sync vs event-driven, SQL vs NoSQL Strong testing practices: pytest, mocking, and integration tests for AI systems Experience with Docker and Kubernetes Hands-on experience building production LLM-based applications and agentic workflows Experience with LLM APIs (OpenAI, Anthropic, or AWS Bedrock) Experience building and optimizing RAG systems Understanding of LLM evaluation techniques and quality assurance approaches Experience deploying and maintaining AI/ML models in production environments Hands-on experience with AWS (SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP considered Experience with React/Vue AWS and Claude Code Certifications Nice to Have Experience with Streamlit or Gradio for AI prototyping Modern Python tooling (ruff, uv, pyproject.toml, pyright) CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, Node.js, or Rust) Front-end experience