Description

Key Responsibilities

AI & Application Development

• Design and implement LLM based systems (RAG, prompt pipelines, structured extraction)
• Build document intelligence pipelines (parsing, validation, enrichment)
• Integrate AI services into production APIs and backend systems
• Ensure robustness around edge cases, retries, and failures

Backend Engineering

• Develop clean, modular Python services (FastAPI/Flask, async workers, batch jobs)
• Design scalable APIs and service layers
• Work with structured and unstructured data (JSON, files, event streams)

Cloud & Infrastructure (Azure First)

• Deploy and manage services on Azure (App Services, Functions, Storage, Service Bus)
• Work with Azure OpenAI and related AI services
• Ensure systems are secure, scalable, and cost efficient

Systems Thinking & Production Readiness

• Design for observability (logging, metrics, tracing)
• Identify and handle failure modes in AI pipelines
• Optimize for latency, throughput, and cost
• Participate in architecture decisions and trade off analysis

Required Qualifications:

Core Engineering

• Strong Python development (production grade code, testing, modular design)
• Experience building backend systems (APIs, workers, pipelines)
• Solid understanding of system design and distributed systems

AI / ML Systems

• Hands on experience building LLM based applications
• Understanding of RAG architectures, prompt design, and structured output extraction
• Experience integrating AI into real production systems (not notebook only)

Cloud & Deployment

• Experience with Azure (or similar cloud, with willingness to work in Azure)
• Familiarity with cloud storage, compute, and event driven architectures

Preferred Qualifications:

• Docker and containerized deployments
• Exposure to Kubernetes
• Vector databases (Pinecone, FAISS, Azure AI Search)
• Async frameworks, background workers, CI/CD pipelines
• Prior work on document processing, workflow automation, or enterprise integrations

Key Skills

Education

Any Gradute