Role Overview
We are seeking an experienced AI‑focused Software Engineer to design, build, and scale intelligent applications powered by modern AI and large language models. This is not a Data Scientist role—we are looking for a strong software engineering professional with deep expertise in building production‑grade AI systems, APIs, and distributed architectures.
Key Responsibilities
• Design and develop Python‑based APIs for AI‑powered applications and services
• Build and orchestrate agentic workflows using modern frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, or LlamaIndex
• Implement and optimize Retrieval‑Augmented Generation (RAG) pipelines
• Develop scalable AI systems leveraging machine learning and deep learning frameworks
• Integrate and manage vector databases (e.g., Pinecone, Weaviate, Chroma) for semantic search and memory
• Architect and deploy applications across cloud platforms (AWS, GCP, Azure)
• Apply domain‑driven design (DDD) principles and build microservices architectures
• Ensure code quality through strong use of object‑oriented programming principles (inheritance, polymorphism) and proven design patterns
• Collaborate cross‑functionally to deliver robust, production‑ready AI solutions
Required Qualifications
• Strong experience in Python software development
• Hands‑on experience with LLM frameworks and orchestration tools (LangChain, LangGraph, AutoGen, etc.)
• Solid understanding of RAG architectures and vector search systems
• Experience working with machine learning frameworks such as TensorFlow or PyTorch
• Proficiency in building and consuming RESTful APIs
• Experience with cloud infrastructure (AWS, GCP, or Azure)
• Strong knowledge of microservices architecture and domain‑driven design
• Deep understanding of object‑oriented programming concepts and software design patterns
Preferred Qualifications
• Experience building agent‑based or autonomous AI systems
• Familiarity with real‑time AI applications and streaming architectures
• Experience optimizing AI systems for performance and scalability
• Exposure to MLOps practices and deployment pipelines
What Success Looks Like
• You deliver scalable, production‑grade AI systems, not prototypes
• You can design complex agentic workflows that solve real business problems
• You write clean, maintainable, and well‑architected code
• You bridge the gap between AI capabilities and software engineering excellence