provectus - Solutions Architect (GenAI, Python/Data, AWS)
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Requirements
• 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 • AI & Python/ Data & Cloud • 7+ years building and running production systems — not only demos and POCs • Hands-on experience building production LLM-based applications and agentic workflows • Experience in integrating AI/ML components into solutions • 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 • Python skills: OOP, design patterns, clean architecture, and performance optimization • Experience building RESTful APIs with FastAPI, Django REST, or Flask • Experience in making and defending architectural trade-off decisions • Hands-on experience with AWS (Bedrock AgentCore, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP considered • Understanding of CI/CD practices applied to ML and AI pipelines • Familiarity with model monitoring, observability, and drift detection. • AWS and Claude Code Certifications • CI/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
Responsibilities
• 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.
Benefits
• Opportunity to work with cutting-edge AI and cloud solutions • Internal training programs (Leadership, Public Speaking, and more) with full support for AWS and other professional certifications • Career growth: a clear path toward SA or beyond; we actively develop our engineers • Access to the latest AI tools and premium subscriptions • Long-term B2B collaboration • Remote with flexible hours • Private medical insurance or a budget for your medical needs • Paid sick leave, vacation, and public holidays • Equipment and all the tech you need for comfortable, productive work
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