We are looking for a Senior AI/ML Engineer to design, build, and deploy production‑grade artificial intelligence solutions that deliver measurable business impact. This role focuses on turning AI concepts into robust, scalable systems that can be adopted and used effectively by real teams and organizations.
You will work closely with AI strategists, data scientists, analysts, and engineers to integrate machine learning and generative AI capabilities into enterprise applications. The role blends strong software engineering foundations with applied AI expertise, and requires comfort operating across the full lifecycle—from design to deployment and adoption.
AI & Application Development
Design, develop, and integrate AI‑powered components into production software systems.
Embed machine learning and generative AI capabilities into applications using modern frameworks and services.
Translate business and user needs into reliable, maintainable AI‑enabled solutions.
Collaborate with data scientists and data engineers to operationalize models and ensure they perform effectively in real‑world environments
System Integration & Architecture
Build software infrastructure that supports AI model integration, orchestration, and lifecycle management.
Apply agent‑based and service‑oriented patterns where appropriate to support complex AI workflows.
Ensure solutions integrate cleanly with existing enterprise systems and data platforms.
Contribute to architectural decisions that balance scalability, performance, and maintainability.
Cloud, DevOps & Deployment
Implement and maintain CI/CD pipelines for AI models and applications.
Assist deployment automation using infrastructure‑as‑code and modern DevOps practices.
Ensure reproducibility, reliability, and observability of AI systems in production.
Support smooth handoff from development to operation
Collaboration & Client Enablement
Work closely with cross‑functional teams to deliver end‑to‑end AI solutions.
Support clients and internal stakeholders in adopting and using AI‑enabled systems.
Clearly communicate technical concepts, trade‑offs, and implementation considerations.
6+ Years of experience in AI/ML Development and Machine Learning
4+ years of experience in Python, SQL, Git, Docker, and working with both relational and NoSQL databases.
4+ years of experience developing and deploying cloud‑based solutions (AWS, GCP, Azure) as well as working with API‑based integrations.
Work experience working with Spark
Strong software development principles (unit testing, clean code, code reviews) and are familiar with MLOps concepts, data infrastructures (Data Lake, Data Warehouse, Blob storage), and database modeling.
Experience with generative AI frameworks and large language models (LLMs) in production
Knowledge of mathematics, statistics, data exploration and visualization, as well as experience in applied machine learning (time series, NLP, computer vision), are considered strong assets.
Comfortable working in Agile or iterative delivery environments.
Nice to Have
Hands‑on exposure to MLOps practices (model versioning, monitoring, CI/CD for ML)
Experience in regulated or privacy‑sensitive environments.
Knowledge of data engineering concepts (data pipelines, feature stores, streaming)
Prior experience supporting multiple products or clients within a shared platform ecosystem.
Experience with marketing technology (MarTech) platforms, such as CDPs, CRMs, marketing automation, or analytics tools
