Solution Architect – Python with GenAI
Job Summary
Our team is expanding and were bringing on a Solution Architect with deep specialization in Python and Generative AI to build and deliver enterprise-grade GenAI solutions ready for real-world production use. Youll be an integral part of our Solution Architecture group spearheading technical exploration efforts crafting reusable frameworks and shaping standards for LLM-based applications. Submit your application to take part in forward-thinking GenAI initiatives and empower clients to achieve breakthrough outcomes.
- Architect complete GenAI systems including RAG frameworks Agents and Multi-Agent configurations tailored for enterprise-level clients
- Develop reusable accelerators and reference builds to bring consistency to delivery approaches
- Facilitate technical discovery workshops while offering direct practical support to engineering teams
- Establish evaluation methodologies and set standards for building large language model (LLM) applications
- Work alongside diverse teams to guarantee system designs that scale effectively and remain easy to maintain
- Build out microservices-based architectures leveraging established design patterns and contemporary frameworks
- Manage the incorporation of cloud infrastructure elements across platforms like AWS Azure or GCP
- Handle containerization and orchestration processes utilizing Docker and Kubernetes
- Assess and choose suitable vector database solutions such as Pinecone Weaviate or Chroma for GenAI use cases
- Deploy LLMOps methodologies and monitoring solutions to fine-tune production-level deployments
- Assist with prompt management and RAG evaluation processes to boost application precision
- Take part in mentoring efforts and knowledge exchange across the broader architecture team
- Maintain high standards of production-ready code quality within Python-based applications
- Push forward ongoing enhancements in system architecture and solution scalability
- Between 9 and 14 years of experience in software development with a strong foundation in solution architecture and system design
- Advanced Python development skills with a focus on writing production-ready code
- Skilled in microservices design architectural patterns FastAPI Redis Elasticsearch and Kafka
- Substantial background building GenAI applications covering Agents MCP RAG Agentic RAG and GraphRAG
- Strong familiarity with LangGraph LangChain and related orchestration tools
- Hands-on background in evaluating LLMs and RAG systems along with managing prompts
- Demonstrated success in delivering scalable GenAI applications ready for production environments
- Working experience with cloud ecosystems such as AWS Azure or GCP
- Comfortable with containerization tools namely Docker and Kubernetes
- Familiarity with vector database technologies including Pinecone Weaviate or Chroma
- Solid grasp of LLMOps principles and associated monitoring solutions
- Strong leadership capabilities suited to directing engineering teams
- Capacity to thrive in client-facing settings while working collaboratively
- Solid English communication skills both written and spoken at B2 level or above
- Experience in conventional machine learning practices including feature engineering model training and evaluation methods
- Familiarity with knowledge graphs along with fine-tuning approaches
- Previous background in consulting positions or client-facing capacities
Required Experience:
Manager