The Role
Design and scale production AI/ML systems, including autonomous agents, LLM integrations, retrieval pipelines, and virtual assistants with voice capabilities. Build and optimize models, training and deployment pipelines, APIs, and cloud-native services. Apply agent frameworks, vector databases, RAG, fine-tuning, observability, and MLOps practices. Collaborate on architecture, evaluate emerging reasoning and tool-use approaches, and mentor engineering peers.
Summary Generated by Built In
This is a remote position.
Job Location: Pakistan (Remote)
Employment type: Full-time
Job timings: US time zone
We are looking for a Senior Software Engineer (AI/ML) who can design, build, and scale intelligent systems — from machine learning pipelines to advanced AI agents capable of reasoning, planning, and automation.
You will work on building production-grade AI models, integrating LLMs and tools, and designing agent architectures that interact with APIs, databases, and workflows. The role blends applied ML expertise with strong backend engineering and product-focused problem-solving.
Responsibilities:
- Design and build autonomous or semi-autonomous AI agents that can plan, reason, and interact with tools, APIs, or external systems
- Implement agentic frameworks (e.g., LangChain, LlamaIndex, CrewAI, or custom orchestration systems)
- leverage existing industry capabilities to deliver virtual assistant capabilities on top of xquic content including voice interactions
- Optimize reasoning and retrieval pipelines using embeddings, vector databases, and prompt engineering
- Develop, train, and fine-tune ML models using frameworks like PyTorch, TensorFlow, or scikit-learn
- Work on data preprocessing, feature engineering, and model evaluation for NLP, computer vision, or predictive tasks
- Build ML pipelines for training, deployment, and monitoring in production environments
- Collaborate with engineering teams to integrate AI components into backend systems and APIs
- Ensure scalable, maintainable codebases with CI/CD, observability, and cloud-native design (AWS/GCP/Azure)
- Contribute to technical architecture and design reviews for AI-driven features and platforms
- Stay current with the latest in LLMs, agent frameworks, and model architectures
- Prototype and evaluate new approaches for reasoning, tool use, and adaptive behavior in agents
- Share learnings and mentor peers in ML and AI development best practices.
Requirements
- Bachelors Degree in Computer Science or related fields
- 5 years of experience
- Strong programming skills in Python (mandatory); proficiency with PyTorch,
- TensorFlow, or transformers-based models
- Experience in building or integrating AI agents (LangChain, LlamaIndex, CrewAI, custom frameworks)
- Strong grasp of ML model lifecycle — data processing, model training, evaluation, deployment, and monitoring
- Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes)
- Familiarity with API integrations, microservices, and asynchronous systems
- Strong understanding of vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) and retrieval architectures
- Solid software engineering fundamentals — testing, version control, and system design
- Experience with LLM fine-tuning, prompt optimization, or RAG (Retrieval-Augmented Generation) systems
- Familiarity with multi-agent systems and coordination mechanisms
- Knowledge of MLOps tools (MLflow, Kubeflow, Sagemaker, Vertex AI)
- Experience in AI system observability, evaluation metrics, and continuous learning loops
- Exposure to reinforcement learning or self-improving agent architectures
Skills Required
- Bachelor’s degree in Computer Science or a related field
- 5 years of professional experience
- Strong programming skills in Python
- Proficiency with PyTorch, TensorFlow, or transformer-based models
- Experience building or integrating AI agents using LangChain, LlamaIndex, CrewAI, or custom frameworks
- Strong understanding of the machine learning lifecycle, including data processing, training, evaluation, deployment, and monitoring
- Experience with AWS, GCP, or Azure
- Experience with Docker and Kubernetes
- Familiarity with API integrations, microservices, and asynchronous systems
- Strong understanding of vector databases and retrieval architectures
- Software engineering fundamentals, including testing, version control, and system design
- Experience with LLM fine-tuning, prompt optimization, or RAG systems
- Familiarity with multi-agent systems and coordination mechanisms
- Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI
- Experience with AI system observability, evaluation metrics, and continuous learning loops
- Exposure to reinforcement learning or self-improving agent architectures
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The Company
What We Do
CloudPSO is an IT outsourcing and software development company that offers custom software engineering, managed cloud services, and cybersecurity solutions to help enterprises optimize costs, scale faster, and innovate with confidence.
