AI Engineer

Job Brief

We are looking for an AI Engineer to join our fast-growing team and help build intelligent, scalable AI-driven products. In this role, you will work end-to-end across the AI lifecycle—from data analysis and model development to deployment and optimization in production.

You’ll collaborate closely with product, engineering, and data teams to turn cutting-edge AI research into real-world systems that deliver measurable business impact.

What You’ll Do

Design, build, and deploy AI-powered systems that solve real-world business problems at scale

Develop, train, and fine-tune machine learning and deep learning models for prediction, classification, and intelligent automation

Build NLP and/or computer vision systems to extract insight from unstructured data such as text, images, audio, or video

Implement LLM-based solutions including prompting strategies, fine-tuning, RAG pipelines, and AI agents

Create scalable inference pipelines optimized for performance, latency, and cost

Work with large, messy, real-world datasets and transform them into reliable, production-grade AI products

Collaborate with data scientists, software engineers, and product managers to integrate AI models into broader system architectures

Deploy, monitor, and maintain AI systems in production, iterating based on user feedback and business metrics

Stay up to date with the latest AI trends and research, and proactively suggest improvements to existing models and workflows

Ensure responsible AI practices, including model explainability, robustness, and fairness

What We’re Looking For

3+ years of hands-on experience building and deploying AI / ML systems in production environments

Strong foundation in machine learning, deep learning, and applied AI concepts

Proficiency in Python and experience with AI/ML frameworks such as PyTorch, TensorFlow, or scikit-learn

Practical experience with LLMs, transformers, embeddings, and modern AI architectures

Experience working with imperfect, real-world data and delivering scalable solutions

Understanding of MLOps concepts such as model versioning, monitoring, and CI/CD for ML

Experience deploying AI systems on cloud platforms like AWS, GCP, or Azure

Strong problem-solving mindset with the ability to translate business requirements into AI-driven solutions

Ability to collaborate effectively in a fast-paced, team-oriented startup environment

Bonus Points

Experience with generative AI, RAG pipelines, vector databases, or AI agents

Knowledge of responsible AI, bias detection, or model explainability techniques

Experience building AI features for SaaS products or high-scale platforms

Familiarity with Java or R in addition to Python

Why Join Us?

Build AI systems that directly impact real users and businesses

Work on cutting-edge AI problems with real-world constraints and data

Collaborate with a fast-moving, product-driven team in a startup environment

Influence the AI roadmap and technical direction of a growing SaaS platform

Competitive compensation, continuous learning opportunities, and long-term career growth