About this role.
Zartis is seeking a Senior AI Software Engineer to join a distributed team developing AI-driven applications for a logistics industry client. The role involves designing and deploying AI-powered applications using Python, integrating machine learning models and AI APIs into scalable backend systems, and collaborating with data scientists and product managers. Candidates need 5+ years of software development experience, strong ML framework skills, cloud platform expertise, and familiarity with LLMs and vector databases. This position offers an opportunity to work on meaningful projects with a global consulting partner.
Role DNA
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Job Complexity
5/5Pace & Pressure
4/5Autonomy Level
4/5Communication Load
4/5Salary analysis
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Core skills
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Cover letter sample
Dear Hiring Manager,
I am excited to apply for the Senior AI Software Engineer position at Zartis. With over 5 years of experience building and deploying AI-driven applications, I have a strong track record of integrating machine learning models into production systems. My expertise in Python, cloud platforms, and containerization aligns well with your requirements.
I am particularly drawn to Zartis's mission of delivering impactful AI solutions and would be thrilled to contribute to your logistics industry project. Thank you for your consideration.
Sample interview questions
I have worked on several projects where I took ML models from research to production. For example, I built a real-time recommendation engine that required optimizing inference latency and handling model versioning. Key challenges included ensuring model consistency, managing dependencies, and setting up monitoring for drift detection. I addressed these by using Docker containers, implementing CI/CD pipelines, and collaborating closely with data scientists to establish clear deployment standards.
I start by understanding the functional and non-functional requirements, such as expected traffic, data volume, and latency. I then design a modular architecture using microservices or event-driven patterns, with APIs for model inference and data ingestion. I consider using managed services like AWS SageMaker or Azure ML for model hosting, and use auto-scaling, caching, and message queues to handle varying loads. I also prioritize observability and security from the outset.
I have built applications using LLMs for tasks like document summarization and chat assistants. I've worked with prompt engineering techniques such as few-shot learning and chain-of-thought to improve outputs, and used vector databases like Pinecone or FAISS for retrieval-augmented generation. I've also designed simple AI agents that combine LLM calls with external tool APIs to automate workflows, always keeping in mind token costs and response validation.
I implement robust testing, including unit tests for code and validation tests for model performance. For deployment, I use infrastructure as code and immutable containers to ensure consistency. I set up monitoring for both system metrics (CPU, memory, latency) and ML-specific metrics (model accuracy, feature drift). I also design for failure with retries, fallback logic, and blue-green deployments to minimize downtime.
In one project, I acted as the bridge between data scientists and backend engineers. The data scientists had trained a model, and I led the effort to productionize it. I worked with them to understand the feature pipeline, then designed a scalable REST API to serve predictions. I facilitated communication by organizing regular syncs and creating clear documentation. This ensured everyone was aligned, and the project was delivered on time with high quality.
The company and our mission:
Zartis is a global AI transformation and technology consulting partner where talented engineers and technologists work on cutting edge innovation. We partner with ambitious organizations to design, build, and scale technology solutions that deliver real impact.
Our teams bring deep expertise in AI driven platforms, secure API architectures, and cloud native engineering. You will work on meaningful projects that accelerate the adoption of advanced technologies, from strategy and discovery through to full product delivery, helping turn complex challenges into measurable outcomes.
With engineering hubs across EMEA and LATAM, and long term partnerships in financial services, healthcare and life sciences, and energy and climate, we offer opportunities to work on projects that truly matter. Here, you will not just build technology, you will drive business impact and grow your career alongside industry leaders.
We are looking for a Senior AI Software Engineer to work on a project in the Logistics Industry.
The project:
Our teammates are talented people that come from a variety of backgrounds. We’re committed to building an inclusive culture based on trust and innovation.
You will be part of a distributed team supporting a supply chain leader that provides expert consulting, specialised software, and managed services to optimise end-to-end logistics operations. In this role, you will help design and develop AI-driven applications, integrating machine learning models into scalable production systems that enable smarter decision-making and solve real business challenges across the logistics domain.
We are looking for someone with good communication skills, ideally with experience making decisions, being proactive, used to building software from scratch, and with good attention to detail. You should be comfortable collaborating with cross-functional teams, contributing to technical and architectural decisions, and delivering high-quality AI-powered solutions in a cloud-based environment.
What you will do:
Design, develop, and deploy AI-powered applications using Python.
Integrate machine learning models, AI APIs, and intelligent algorithms into scalable backend systems.
Collaborate with data scientists, product managers, and software engineers to define, develop, and deliver AI-driven features.
Contribute to software architecture, system design, and technical decision-making for AI-enabled products.
Develop and maintain CI/CD pipelines and containerized environments using Docker.
Deploy and manage AI applications on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
Optimize AI solutions for scalability, performance, reliability, and maintainability.
Stay up to date with the latest advancements in AI, machine learning, and emerging technologies, evaluating opportunities to incorporate them into products and workflows.
What you will bring:
Bachelor’s degree in Computer Science, Software Engineering, or a related field.
5+ years of professional software development experience, with a focus on integrating AI/ML solutions into production applications.
Strong programming skills in Python (preferred) or Java.
Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, or Hugging Face Transformers.
Solid understanding of machine learning concepts, data engineering, ETL processes, and model deployment.
Experience working with SQL and large-scale datasets.
Familiarity with containerization (Docker), CI/CD practices, and cloud platforms (AWS, Azure, or GCP).
Experience building or consuming RESTful APIs and integrating AI services into enterprise applications.
Experience working with LLMs , vector databases, prompt engineering, or AI agents.
Strong analytical and problem-solving mindset
Excellent communication and collaboration skills
Proactive, adaptable, and self-driven Ability to work independently and collaboratively within cross-functional teams
Genuine motivation to contribute to organizations success and alignment with its culture and values.
Nice to have:
Experience with modern frontend frameworks such as React, Angular, or Vue.js.
Knowledge of MLOps tools and practices
Familiarity with Kubernetes, infrastructure as code, or microservices architectures.
What we offer:
100% Remote Work
WFH allowance: Monthly payment as financial support for remote working.
Career Growth: We have established a career development program accessible for all employees with a 360º feedback that will help us to guide you in your career progression.
Training: For Tech training at Zartis, you have time allocated during the week at your disposal. You can request from a variety of options, such as online courses (from Pluralsight and Educative.io, for example), English classes, books, conferences, and events.
Mentoring Program: You can become a mentor in Zartis or you can receive mentorship, or both.
Zartis Wellbeing Hub (Kara Connect): A platform that provides sessions with a range of specialists, including mental health professionals, nutritionists, physiotherapists, fitness coaches, and webinars with such professionals as well.
Multicultural working environment: We organize tech events, webinars, parties, and activities to do online team-building games and contests.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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