Solutions Architect

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 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 Experience with Docker and Kubernetes 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 Nice to Have 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 What We Offer: 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 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