Software Engineer I - AI/ML & Backend Engineering

In this role, you will design, build, and deploy production-grade AI applications for international clients across diverse business domains. Working in a fast-paced, client-focused services environment, you will bridge the gap between cutting-edge Machine Learning/Generative AI models and enterprise backend software architectures. You will develop Retrieval-Augmented Generation (RAG) pipelines, construct autonomous Agentic AI workflows (LangChain, LangGraph, LlamaIndex), build scalable RESTful APIs (FastAPI, Flask, Django), and integrate vector databases for real-world semantic search systems.

Key Responsibilities

AI/ML & Generative AI Development

• Generative AI & LLM Integrations: Build and integrate GenAI applications using leading Large Language Models (OpenAI, Anthropic, Gemini, and open-source models) via prompt engineering and API orchestrations.
• RAG & Vector Search: Design and maintain Retrieval-Augmented Generation (RAG) pipelines paired with vector databases (Pinecone, FAISS, ChromaDB, Weaviate) for semantic retrieval.
• Agentic AI Workflows: Build multi-agent systems and intelligent workflows leveraging frameworks such as LangChain, LangGraph, or LlamaIndex.
• Classical ML & Deep Learning: Implement and fine-tune traditional machine learning and deep learning architectures using Scikit-learn, TensorFlow, or PyTorch.

Python Backend & Systems Engineering

• API & Microservice Development: Develop scalable, low-latency Python backend services and RESTful APIs utilizing FastAPI, Flask, or Django.
• Data Engineering: Perform data collection, preprocessing, feature extraction, embedding generation, and model evaluation routines.
• Database Architecture: Interact with relational and non-relational database layers, including PostgreSQL, MySQL, and MongoDB.
• DevOps & Cloud Integration: Package microservices using Docker, collaborate via Git/CI/CD pipelines, and support deployment onto cloud platforms (AWS, Azure, GCP).
• Engineering Excellence: Write clean, modular, reusable, and well-documented Python code following object-oriented design and algorithm optimization.
• Client & Cross-Functional Collaboration: Participate in code reviews, technical discovery, and agile sprints while communicating technical solutions clearly in English to global stakeholders.

Requirements

Education, Technical Skills & Domain Depth

• Education: Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical discipline.
• Experience Track: Minimum 1.5+ years of professional post-graduation software engineering experience focused on AI/ML development.
• Core Python Mastery: Strong proficiency in Python, Object-Oriented Programming (OOP), Data Structures & Algorithms (DSA), and logical problem-solving.
• Generative AI & Agentic Stack: Hands-on experience constructing RAG architectures and multi-step AI agents (LangChain, LangGraph, LlamaIndex).
• ML & Deep Learning Frameworks: Practical experience training, testing, or fine-tuning models with Scikit-learn, PyTorch, or TensorFlow.
• Backend Frameworks: Hands-on experience developing production APIs using FastAPI, Flask, or Django.
• NLP & Vector Stores: Understanding of NLP fundamentals, transformers, embedding spaces, and vector database engines (Pinecone, FAISS, ChromaDB, Weaviate).
• Tooling & Cloud: Working familiarity with Git version control, Docker containerization, CI/CD routines, and public cloud environments (AWS, Azure, GCP).
• Communication: Excellent verbal and written English communication skills to articulate complex engineering choices to international clients and internal engineering pods.

Total Rewards & Benefits

• Market-Competitive Salary: Salary aligned with industry standards for junior-to-mid level AI/ML software engineers in Pakistan.
• Global Project Exposure: Direct experience building production software for enterprise clients across North America, Europe, and the Middle East.
• Mentorship & Career Progression: Structured internal training, tech talks, and clear advancement paths within Devsinc's engineering tiers.
• Collaborative Culture: Vibrant, fast-paced work environment equipped with modern hardware setups, team outings, and professional growth opportunities.