Role Summary
We are seeking a
Senior AI / Generative AI Python Developer to design and build intelligent enterprise applications that support data modernization and cognitive solutions within a complex financial platform environment.
The role involves developing
LLM-powered applications, RAG pipelines, conversational AI systems, and AI agents, integrating enterprise data sources, and deploying scalable AI services on cloud platforms.
Key ResponsibilitiesAI / GenAI Solution Development
- Design and develop AI/ML and Generative AI applications using Python.
- Build and deploy LLM-powered solutions including RAG pipelines, AI agents, and multi-agent systems.
- Develop document intelligence pipelines for structured and unstructured data (PDF, Office files).
LLM & AI Integration
- Integrate OpenAI / Azure OpenAI and other foundation models.
- Implement semantic search and vector-based retrieval systems.
- Design and develop conversational AI chatbots with contextual memory.
Agentic AI & Orchestration
- Develop Agent-based AI systems using LangChain and LangGraph.
- Implement Model Context Protocol (MCP) based integrations for secure AI tool interactions.
- Build multi-agent orchestration workflows.
API & Cloud Deployment
- Build REST APIs using FastAPI or Flask.
- Deploy AI applications on cloud platforms such as Azure or AWS.
- Implement CI/CD pipelines and monitoring for AI services.
Collaboration & Agile Delivery
- Work closely with development teams and technical leads in an Agile delivery environment.
- Integrate AI solutions with enterprise platforms and data systems.
Required Skills Core Skills
- Strong proficiency in Python development.
- Experience with Generative AI frameworks such as LangChain and LangGraph.
- Hands-on experience with RAG architectures and vector databases.
- Experience integrating OpenAI / Azure OpenAI APIs.
AI / NLP
- Knowledge of Natural Language Processing and Document Intelligence.
- Prompt engineering and LLM optimization.
- Experience designing AI chatbots and conversational systems.
Backend & Integration
- REST API development using FastAPI / Flask.
- Microservices architecture and scalable backend systems.
Cloud
- Experience deploying AI applications on Azure or AWS.
- Familiarity with CI/CD pipelines and cloud monitoring.
Preferred Skills
- Experience building enterprise AI copilots.
- Exposure to multi-agent orchestration systems.
- Knowledge of Model Context Protocol (MCP) architecture.
- Experience integrating AI with SharePoint or Dataverse.
- Understanding of AI governance, evaluation, and monitoring.
Skills: python,openai,azure,mlops,llm,cloud,genai,ai/ml