Tech Lead Architect – Python, Gen AI
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Job Location:
Monthly Salary:
Posted on:
9 days ago
Vacancies:
1 Vacancy
Job Summary
Tech Lead / Architect - Python Applications with GenAI Integration
We are seeking a highly experienced Tech Lead / Architect to drive the architecture and delivery of modern scalable data applications powered by Generative AI (GenAI). This role focuses on solution design architectural leadership and cross-functional collaboration across AI/ML platforms backend engineering and cloud-native infrastructure.
While we are not looking for hands-on AI/ML development candidates must demonstrate deep architectural understanding of the GenAI stack. A strong hands-on background in developing Python-based applications is essential.
Roles and Responsibilities
- Lead the end-to-end architecture and design of Python-based applications integrated with GenAI capabilities.
- Translate business and product requirements into modular scalable and maintainable technical solutions.
- Guide and mentor backend infrastructure and MLOps teams in implementing architecture blueprints.
- Evaluate and recommend the right mix of tools frameworks and platforms - including LLM providers vector databases and cloud-based ML services.
- Ensure the security scalability and performance of all deployed systems.
- Stay current with advancements in GenAI and proactively bring relevant capabilities into solution design.
Skills and Qualifications:
- 8 years of experience in software engineering with a minimum of 4 years in a technical leadership or architecture role.
- Proven track record in building robust Python-based backend systems using frameworks such as FastAPI Flask or Django.
- Expertise in microservices architecture distributed system design and integration patterns.
- Strong familiarity with cloud platforms such as AWS Azure or GCP and practical knowledge of AI/ML services like SageMaker Vertex AI or Azure ML.
- Architectural experience with vector databases (e.g. Pinecone FAISS Weaviate Qdrant) for semantic search and RAG pipelines.
- Understanding of DevOps practices including Docker Kubernetes and infrastructure as code.
- Knowledge of CI/CD processes system security and observability/monitoring frameworks.
GenAI & AI/ML Architecture Expertise:
- Sound understanding of GenAI system components including LLM lifecycles embedding generation prompt orchestration and RAG architectures.
- Ability to architect complete GenAI workflows from context ingestion and enrichment to inference handling and post-processing.
- Familiarity with API orchestration agent-based design patterns and semantic search strategies.
- Direct data science work isnt required but a solid understanding of AI/ML engineering principles and pipeline design is essential to ensure the architecture supports model and data requirements.
Required Skills:
Python
Key Skills
- APIs
- Docker
- Jenkins
- REST
- Python
- AWS
- NoSQL
- MySQL
- JavaScript
- Postgresql
- Django
- GIT
