Job Description

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