Solutions Architect

Role Description

• 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.

Qualifications

• 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.

Requirements

• 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.
• 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.

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.