Senior AI / LLM Engineer (GenAI Systems)
Bluegeko
$ 2,200 • Published Date: • Lahore, Pakistan (On-Site)
Description
We are building a next-generation AI infrastructure platform focused on LLMs, intelligent matching, and scalable AI systems.
We are looking for an experienced Senior AI / LLM Engineer to design, build, and deploy production-ready AI solutions across models, infrastructure, and applications.
You will take ownership of core AI development while leading and mentoring a small team of Junior AI Engineers.
Tech Stack & Skills:
You don't need everything — strong expertise in a few areas matters most.
- Software Engineering: Python, CI/CD, Git, containers, APIs, databases.
- Machine Learning: PyTorch, TensorFlow, Keras.
- LLMs & GenAI: RAG, LangChain, vector databases, embeddings.
- LLM Integration: Function calling, structured outputs, prompt engineering.
What We're Looking For:
- Proven experience building and deploying LLM or ML systems in production.
- Strong understanding of modern AI architectures and transformer-based models.
- Ability to work across models, infrastructure, and product development.
- Strong problem-solving skills and the ability to deliver real solutions.
- Ability to lead, mentor, and review the work of junior engineers.
Nice to Have (Not Required):
- NLP: NER, classification, information extraction, semantic analysis.
- MLOps & Inference: CUDA, vLLM, Ollama, Triton, DeepSpeed, FSDP.
- Model Training: Fine-tuning (SFT, DPO), dataset preparation and curation.
- Education: Master's or PhD in AI, ML, or a related field.
Career Growth & Opportunities:
- Bring your own ideas and directly influence technical decisions.
- Take ownership of core AI systems and architecture.
- Opportunity to grow into a larger technical leadership role as the company scales.
- Regular performance and salary reviews based on results and contributions.
We want a hands-on builder and systems thinker who can take ownership, move quickly, and deliver production-ready AI solutions in a growing technology company.
Responsibilities
- Design, build, and scale end-to-end AI pipelines from data ingestion to production deployment.
- Develop and deploy reliable, scalable LLM-powered applications and systems.
- Optimize model inference speed, performance, and infrastructure efficiency.
- Architect RAG systems, AI agent workflows, and structured output pipelines.
- Improve prompt engineering, NLP workflows, and data quality.
- Lead and manage a small team of Junior AI Engineers, providing technical guidance, code reviews, and mentorship.
- Integrate LLM frameworks, vector databases, embeddings, and external APIs.
- Apply software engineering best practices, including CI/CD, Git, containerization, and testing.
- Collaborate with product and engineering teams to deliver practical AI solutions.
- Research and evaluate emerging AI technologies, frameworks, and model architectures.
- Identify technical improvements and independently drive AI development initiatives.
Experience
4 Years
Apply By
Required Skills
- APIs
- Model Deployment
- Inference optimization
- Prompt Engineering
- Embeddings
- Retrieval Augmented Generation (RAG)
- Large Language Model Architecture
- Containers
- Git
- CI/CD
- Tensorflow
- PyTorch
- Python
- Natural Language Processing
Nice to Have Skills
- Databases
- Keras
- Langchain
- Vector Databases