Solutions Architect; AI, Python​/Data

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 Agent Ops 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.

• 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.

• 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 Agent Core, 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 (Git Hub Actions, Git Lab CI).
• Experience in an additional language (Go, Node.js, or Rust).
• Hands‑on experience with Apache Spark, Apache Airflow, Kafka.

• 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.