AI & Software Engineer

Professional Summary

Senior AI & Software Engineer with experience in designing and building scalable AI-powered applications, backend systems, and intelligent automation solutions. Skilled in developing production-grade software using Python, modern AI frameworks, RESTful APIs, workflow automation, and cloud-native technologies. Experienced in integrating AI capabilities into business processes through LLMs, RAG pipelines, autonomous agents, and automation workflows while maintaining clean architecture, performance, and scalability.

Core Responsibilities

• Design, develop, and deploy AI-powered software solutions using Large Language Models (LLMs), NLP techniques, embeddings, and information retrieval.
• Build intelligent automation workflows by integrating AI services with backend systems, APIs, databases, and third-party platforms.
• Develop autonomous and semi-autonomous AI agents with tool integration, workflow orchestration, and state management.
• Design and implement Retrieval-Augmented Generation (RAG) systems using semantic search, hybrid retrieval, and reranking techniques.
• Build scalable backend services and RESTful APIs using Python and FastAPI following software engineering best practices.
• Develop asynchronous processing pipelines and event-driven architectures for AI and automation workloads.
• Design and optimize relational and vector databases, including schema design, indexing, caching, and query optimization.
• Collaborate on distributed system architecture to ensure scalability, fault tolerance, and maintainability.
• Containerize applications with Docker and manage source code using Git and collaborative development workflows.
• Integrate automation platforms, messaging systems, and business workflows to streamline operational processes.

Technical Skills

• Programming: Python, SQL
• AI & Machine Learning: LLM Applications, NLP, Prompt Engineering, RAG, AI Agents, Embeddings, Model Integration
• Automation & Integration: Workflow Automation, API Integration, Event-Driven Architecture, Background Processing, Task Scheduling
• Backend: FastAPI, REST APIs, Async Programming, Microservices
• Databases: PostgreSQL, Qdrant, Milvus, pgvector, Redis
• Infrastructure: Docker, Git, Linux

Additional Experience

• Building intelligent business automation solutions powered by AI.
• Designing scalable backend architectures for AI and automation platforms.
• Integrating AI models with enterprise systems and third-party services.
• Experience with asynchronous task queues (Celery, RabbitMQ, Redis).
• Familiarity with Kubernetes and cloud deployment.
• Experience with AI evaluation and observability tools (LangSmith, Ragas, Phoenix).