AI & Backend Engineer

. Design, build, and deploy AI systems, including LLMs, RAG, agentic workflows, and ML/DL solutions.

Posted 9/26/2026full-timeIslamabad • PakistanMid-LevelSenior💰 PKR 150,000 - PKR 400,000 per monthWebsite

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKerasKubernetesPyTorchSQL

Key responsibilities & impact

Design, build, and deploy AI systems, including LLMs, RAG, agentic workflows, and ML/DL solutions.
Select appropriate models and architectures while balancing accuracy, latency, cost, and complexity.
Train and fine-tune models using PyTorch or Keras, including data preparation and evaluation.
Implement and benchmark research methods before adoption.
Build APIs, inference pipelines, and backend integrations.
Own evaluation metrics and track quality, latency, and cost.
Monitor, debug, and optimize AI systems post-launch.
Ensure production readiness and identify regressions before they impact users.
Partner with software engineers and product teams to integrate AI into applications.
Contribute to technical discussions and technical decision-making.
Document architecture, implementation approaches, and key technical decisions.
Read and evaluate ML research papers.
Implement promising methods and reproduce results where applicable.
Adapt emerging techniques into production-ready systems.
Contribute to continued innovation across AI and engineering initiatives.
Collaborate with engineering leadership, product teams, software engineers, backend developers, and global AI research and development teams.
Deliver production-ready AI systems with measurable impact.
Translate research into practical engineering solutions.
Document and share technical knowledge for scalability.

What you’ll need

3+ years of hands-on AI/ML engineering experience, with at least one system deployed to production.
Strong NLP fundamentals, including tokenization, embeddings, classification, NER, and information extraction.
Strong engineering skills across coding, Git, testing, API/system design, and debugging.
Hands-on model training experience using PyTorch or Keras.
Understanding of generative model architectures, including Transformers and VAEs.
Production experience with LLMs, including RAG, embeddings/vector databases, and prompt/evaluation design.
Experience with FastAPI or similar frameworks, Docker, and at least one cloud platform such as AWS, GCP, or Azure.
Ability to read ML research papers and translate ideas into working code.
Preferred: Experience with LLM fine-tuning, including LoRA and RL-based methods.
Preferred: SQL database knowledge.
Preferred: Familiarity with agent frameworks such as LangGraph or LangChain.
Preferred: Experience with Kubernetes, CI/CD, and model-serving infrastructure.
Preferred: Open-source contributions or experience reproducing research results.
Working hours: 07:00 PM – 04:00 AM PKT.

Comp & perks

Team members will be engaged by Volga Partners, with contract and payment administration facilitated through Deel.
90-day probationary period.
Company-sponsored medical insurance.
Paid Time Off (PTO) in accordance with company policy.
Holiday pay for company-observed holidays.
Career growth and professional development opportunities within Volga Partners’ growing AI-focused organization.