Artificial Intelligence (AI) Engineer

We are looking for a talented Artificial Intelligence Engineer to join our dynamic engineering team. The successful candidate will design and develop intelligent, scalable, and production-ready AI solutions that enhance our business products and web applications. This role requires hands-on experience with Python, Machine Learning, Generative AI, Large Language Models (LLMs), AI APIs, and AI application development. You will collaborate closely with software engineers, product managers, and other stakeholders to integrate AI-powered features and deliver practical AI solutions. Strong software engineering skills combined with AI/ML expertise, problem-solving abilities, and research-driven implementation are essential for success in this position. The role is based in Faisalabad, Karachi, or Hyderabad, Pakistan, and requires a minimum of two years of relevant experience.

Key Responsibilities
- Design, develop, and maintain AI-powered applications and features.
- Integrate Machine Learning and Generative AI solutions into production environments.
- Work extensively with Large Language Models (LLMs) and AI APIs to create business solutions.
- Build AI-powered chatbots, assistants, automation workflows, recommendation systems, and other intelligent applications.
- Implement prompt engineering, structured outputs, function calling, and AI workflows.
- Design and deploy Retrieval-Augmented Generation (RAG) solutions using business and product data.
- Utilize embeddings, vector databases, semantic search, and document-processing pipelines.
- Integrate AI models with REST APIs, backend systems, databases, and third-party platforms.
- Develop and maintain data-processing and AI/ML pipelines.
- Evaluate AI-generated outputs for accuracy, relevance, consistency, and reliability.
- Research and assess new AI models, frameworks, APIs, and technologies for practical use.
- Optimize AI solutions for performance, scalability, latency, reliability, and cost-efficiency.
- Troubleshoot and resolve technical issues in AI applications and production environments.
- Collaborate with cross-functional teams including software engineers, product managers, and designers.
- Participate in code reviews and contribute to technical architecture and engineering decisions.
- Maintain clear technical documentation for AI models, workflows, APIs, experiments, and implementations.

Required Qualifications
- Strong proficiency in Python programming.
- Solid understanding of Machine Learning concepts and workflows.
- Hands-on experience with Generative AI and LLM-based applications.
- Experience working with AI APIs such as OpenAI, Google Gemini, Anthropic, or similar platforms.
- Expertise in prompt engineering and structured AI outputs.
- Knowledge of embeddings, semantic search, and vector databases.
- Practical experience with RAG-based applications.
- Familiarity with AI/ML frameworks like LangChain, LlamaIndex, Hugging Face, PyTorch, or TensorFlow.
- Experience developing and consuming RESTful APIs.
- Working knowledge of SQL and/or NoSQL databases.
- Understanding of data preprocessing, transformation, and validation techniques.
- Proficiency with Git and collaborative software development workflows.
- Awareness of authentication, authorization, and secure API integration.
- Familiarity with Docker and deployment workflows.
- Strong grasp of supervised and unsupervised learning, classification, regression, clustering, and model evaluation.
- Understanding of NLP, text-processing techniques, neural networks, deep learning fundamentals, Transformers, and attention mechanisms.
- Knowledge of LLM architecture and practical application development.
- Experience with model evaluation, performance measurement, and handling AI-specific challenges such as hallucinations, prompt injection, and output validation.
- Ability to select AI models based on accuracy, performance, scalability, and cost considerations.
- Excellent problem-solving and analytical skills.
- Ability to translate business requirements into practical AI solutions.
- Strong programming and debugging capabilities.
- Self-motivated with the ability to research and learn emerging AI technologies independently.
- High attention to detail and ownership of assigned projects.
- Excellent communication and collaboration skills, including fluency in English.
- Ability to explain complex AI concepts clearly to non-technical stakeholders.

Preferred Qualifications and Benefits
- Experience working with SaaS or product-based technology companies.
- Proven track record of deploying AI/ML applications in production environments.
- Familiarity with Hugging Face and open-source LLMs.
- Experience with vector databases such as Pinecone, Qdrant, Weaviate, Chroma, or FAISS.
- Knowledge of cloud platforms like AWS, Azure, or GCP.
- Experience with Docker and CI/CD pipelines.
- Understanding of microservices architecture.
- Experience developing AI agents and multi-step AI workflows.
- Exposure to computer vision or advanced NLP applications.
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.

The interview process includes an initial screening call, a technical assessment focused on Python, AI/ML, and problem-solving, followed by a technical interview covering AI/ML, LLMs, APIs, and system design. Candidates will also participate in a practical AI development and architecture discussion before the final round.