Solutions Architect - AI, Python/Data
New
North America, LATAM, and EMEAFull-TimeMiddle
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Languages
- B2+ English
- Experience
- 7+ years
- Required Skills
- AWSDockerPythonArtificial IntelligenceETLFlaskKubernetesFastAPICI/CDRESTful APIsAWS LambdaLLMMLOpsGenerative AI
Requirements
- 7+ years building and running production systems
- 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)
- Understanding of CI/CD practices applied to ML and AI pipelines
- Familiarity with model monitoring, observability, and drift detection
- B2+ English proficiency
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
- 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
View Full Description & ApplyYou'll be redirected to the employer's site
