AI Engineer | Pakistan

Volga Partners is seeking an experienced AI Engineer to join our Engineering team in Islamabad, Pakistan. This hybrid role requires working three days in the office and two days remotely, with working hours from 7:00 PM to 4:00 AM PKT. The AI Engineer will be responsible for designing, developing, and deploying advanced AI systems, including large language models (LLMs), retrieval-augmented generation (RAG) frameworks, agentic workflows, and intelligent automation solutions. The ideal candidate will have strong hands-on experience in model training, research-to-production skills, and the ability to integrate AI technologies into scalable applications for global clients. This position reports directly to Product and Engineering Leadership.

Key Responsibilities

Design, build, and deploy AI systems such as LLMs, RAG frameworks, agentic workflows, and machine learning/deep learning solutions. Select suitable models and architectures by balancing accuracy, latency, cost, and complexity. Train and fine-tune models using frameworks like PyTorch or Keras, including data preparation and evaluation. Implement and benchmark research methods before adoption, and develop APIs, inference pipelines, and backend integrations.

Own evaluation metrics to monitor quality, latency, and cost. Debug, optimize, and maintain AI systems post-launch to ensure production readiness and prevent regressions. Collaborate closely with software engineers, product teams, and leadership to integrate AI into applications. Participate in technical discussions, decision-making, and document architecture, implementation approaches, and key technical decisions.

Stay current with ML research by reading and evaluating papers, implementing promising methods, and reproducing results where applicable. Adapt emerging techniques into production-ready systems and contribute to ongoing innovation across AI and engineering initiatives.

Required Qualifications

A minimum of 3 years of hands-on AI/ML engineering experience, with at least one system deployed to production. Strong fundamentals in natural language processing (NLP), including tokenization, embeddings, classification, named entity recognition (NER), and information extraction. Proficient engineering skills in coding, version control (Git), testing, API and system design, and debugging. Hands-on experience training models using PyTorch or Keras.

Understanding of generative model architectures such as Transformers and variational autoencoders (VAEs). Production experience with LLMs, including RAG, embeddings/vector databases, and prompt/evaluation design. Familiarity with FastAPI or similar frameworks, Docker, and at least one major cloud platform (AWS, GCP, or Azure). Ability to read and translate ML research papers into working code.

Preferred Qualifications and Benefits

Experience with LLM fine-tuning techniques, including LoRA and reinforcement learning-based methods. Knowledge of SQL databases and familiarity with agent frameworks like LangGraph or LangChain. Experience with Kubernetes, CI/CD pipelines, and model-serving infrastructure. Contributions to open-source projects or experience reproducing research results is a plus.

The monthly salary ranges from PKR 150,000 to PKR 400,000, commensurate with experience and expertise. Employment will be managed through Volga Partners with contract and payment administration facilitated via Deel. A 90-day probationary period applies, after which employees become eligible for company-sponsored medical insurance, paid time off according to company policy, holiday pay for observed holidays, and opportunities for career growth within Volga Partners’ expanding AI-focused organization.

Our Hiring Process

The recruitment process begins with an initial video call with a recruiter to discuss your background, experience, career goals, and salary expectations. Successful candidates will then complete a practical skills assessment asynchronously, designed to evaluate technical knowledge and problem-solving abilities. Submissions are reviewed against the role’s technical requirements, and qualified candidates advance to a final interview with the Chief Technology Officer. This interview focuses on technical alignment, architectural thinking, problem-solving, and overall fit with the team and role.