Job Summary
Key Responsibilities
2. Create automation scripts using python to streamline software development and deployment processes
3. Collaborate within team to integrate devops best practices into project workflows
4. Manage version control systems, particularly github, to ensure code quality and versioning control
5. Troubleshoot and resolve any issues related to devops tools and processes
6. Stay updated with the latest trends and technologies in devops to recommend improvements and enhancements
Skill Requirements
Required Skills
Strong proficiency in Python and backend AI development.
Experience with LLMs (Azure OpenAI, Gemini, etc.) and any Agent development kit.
Knowledge of embeddings (Sentence-Transformers, OpenAI Embeddings, etc).
Hands-on experience with vector DBs like Pinecone, Qdrant, Weaviate, Chroma, FAISS, etc.
Familiarity with hybrid search tools such as Azure AI Search, OpenSearch or similar.
Experience deploying applications on cloud PaaS/IaaS or Kubernetes.
Working knowledge of CI/CD and LLM/MLOps practices.
Nice to Have
Experience with evaluations, prompt engineering, fine-tuning and agent workflows.
Other Requirements
Responsibilities
Develop solutions using LLMs (Azure OpenAI, Google Gemini, OpenAI APIs or similar) and Agent Development Kits (OpenAI Agent SDK/Google ADK/Langchain/Langraph).
Build RAG pipelines using LangChain, LlamaIndex, or similar tools.
Implement document processing, embeddings, vector search, and hybrid semantic search.
Deploy GenAI applications on Azure ML Studio, Vertex AI, AWS, or using FastAPI + Docker/Kubernetes.
Integrate CI/CD workflows using GitHub Actions, Azure DevOps, etc.
Collaborate with product and engineering teams to deliver scalable, secure, and high-performance AI systems.