Solutions Architect (AI, Python/Data)
TLDR
Design and build cloud-native data and AI solutions, optimizing RAG systems and mentoring engineers while owning client engagements from discovery through delivery.
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Design and build cloud-native data, LLM-based, and agentic AI solutions addressing real client business challenges
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Implement and optimize RAG systems for production use cases
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Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor.
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Support presales: discovery calls, technical proposals, scoping, and client-facing demos
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Own the technical direction of client engagements from discovery through delivery — the go-to authority for clients and the internal team
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Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs
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Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools.
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Deploy ML and LLM-based solutions
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Implement MLOps, LLMOps, and AgentOps practices: CI/CD, automated testing, model monitoring, and experiment tracking.
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Lead architecture reviews, produce technical design documents, and contribute to standards
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Mentor engineers, lead code reviews, and share knowledge across the team.
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.
- 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
Nice to Have
Provectus builds robust machine learning infrastructure and production-grade solutions that empower companies to leverage AI and transform their operations and competitive strategies. We cater to businesses facing complex ML challenges, delivering innovative technology that drives significant value and societal impact.
- Founded
- Founded 2010
- Employees
- 500+ employees
- Industry
- Professional Services