Senior - AI Engineer
At a glance
Senior AI Engineering role at NorthBay Solutions. Islamabad · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build predictive models, forecasting tools and reporting systems to inform business decisions
- Write scripts and queries to extract, process and visualize data, and build pipelines that reduce latency
- Put scalable AI and machine-learning solutions into production, then improve their reliability and performance
- Develop agentic workflows and RAG systems, and organize, test and refine generative AI initiatives
- Create evaluation frameworks and integrate open-source models across object detection, classification, OCR and statistical modeling
What you bring
- A computer science bachelor's degree and at least four years of professional technology experience
- At least two years focused on AI or machine learning, including predictive model development
- Production-level Python skills, strong SQL ability and experience with vector databases
- Hands-on work with LLMs, agentic workflows, RAG and prompt engineering, including debugging unpredictable systems
- Experience shipping AI to production and building hallucination checks and evaluation methods
Who this fits
This senior role suits someone who has taken AI systems beyond experiments and can work with stakeholders to turn business needs into technical solutions. The position is full-time and hybrid in Islamabad, Pakistan.
From the employer
Job Title: Senior AI Engineer
Location: Islamabad
Job Type: Full-time, (Hybrid)
Job Description:
NorthBay is seeking a highly skilled AI Engineer with strong experience in AI and advanced analytics to join our team. The ideal candidate will have a solid background in data processing, predictive modeling, and production-grade AI systems. This role requires hands-on expertise in building, deploying, and scaling AI solutions that drive real business impact. You will work closely with cross-functional teams and stakeholders to understand business needs, develop intelligent systems, and deliver actionable insights. A strong focus on modern AI practices, including LLMs and agentic workflows, is essential.
Responsibilities
● Develop a deep understanding of business domains and customer data
● Build predictive models and reporting systems to support decision-making
● Write efficient scripts and queries for data extraction, processing, and visualization
● Design and deploy scalable AI/ML solutions into production environments
● Work on GenAI initiatives, including organizing, testing, and improving AI-driven systems
● Develop and optimize agentic workflows and RAG-based systems
● Design and implement forecasting models to significantly improve accuracy
● Debug and enhance AI systems, focusing on reducing hallucinations and improving reliability
● Build evaluation frameworks to continuously assess and improve AI performance
● Research and integrate state-of-the-art open-source AI models
● Train and optimize models across domains such as object detection, classification, OCR, and statistical modeling
● Build robust data pipelines and integration architectures for improved performance and reduced latency.
● Collaborate with stakeholders to translate business needs into technical solutions
Requirements:
● BS in Computer Science (BSCS) from a reputable university
● 4–6+ years of total professional experience in technology
● 2–3+ years of focused experience in AI/ML
● Strong expertise in data processing, structuring, and visualization
● Proven experience in designing and implementing predictive models
● Production-grade proficiency in Python; .NET is a plus
● Strong SQL skills and experience working with Vector Databases
● Proven ability to ship AI solutions to production (not limited to experimental work)
● Hands-on experience with Large Language Models (LLMs)
● Experience with agentic workflows, Retrieval-Augmented Generation (RAG), and prompt engineering.
● Ability to debug non-deterministic AI systems
● Experience implementing hallucination detection mechanisms
● Strong understanding of evaluation frameworks for AI models and prompts