We fuse together exceptional talent who deliver outstanding software solutions. Our approach has helped us grow 60% in 2021, 94% in 2022, while in 2023 we joined forces with Insight, a Fortune 500 company and a leading solutions and systems integrator. With exciting growth plans and cutting-edge projects, there has never been a better time to join our incredible team.

We are establishing a AI Engineering team who will work closely with our most strategic customers to deeply understand their use cases and design, build, and implement products for them. As one of our founding AIs, you will deploy these solutions on the latest infrastructure for the world's most influential businesses, driving real business impact through the newest models and our own innovations in technical delivery.

AI Engineers' responsibilities look similar to those of a hands-on AI startup CTO: you'll work in small teams to own delivery of high stakes projects with clients. A day's work may include building LLM workflows on a large scale, interacting with customers to understand their needs and set their AI strategy, but the most impact will be driven by implementing solutions into the real world of our partner's organizations.

We are looking for customer-focused software engineers to build effective custom software that leverages leading AI models and technology to solve real customer problems. You will partner directly with customers to conceptualize, design, and implement cutting-edge AI solutions. This role focuses on leveraging generative AI models, agentic systems, and iterative prototyping to build impactful proofs of concept (PoCs) that address unique business challenges. The AI engineer acts as a bridge between advanced AI technologies and practical enterprise applications, ensuring that solutions are both innovative and actionable.

You will collaborate closely with Sales, Solutions Engineering, Solutions Architects, and Customer Success Managers who work on the same account. You will also be self driven to learn about the AI market and bring forward that knowledge to improve the way in which we deliver to customers.

Responsibilities

Customer Engagement:

Collaborate deeply with clients to understand their strategic objectives, technical requirements, and operational constraints.

Serve as a trusted advisor for AI strategy, guiding clients through the process of ideating and implementing generative and agentic AI solutions.

Facilitate workshops and brainstorming sessions to identify high-value use cases for AI technologies.

AI Solution Development:

Design, prototype, and deploy AI-powered PoCs using generative models (e.g., GPT, DALL-E) and agentic systems tailored to specific client needs.

Build end-to-end pipelines for deploying AI solutions on client infrastructure, ensuring scalability, security, and performance.

Experiment with cutting-edge methods in natural language processing (NLP), computer vision, reinforcement learning, and multi-agent systems to deliver innovative solutions.

Iterative Prototyping:

Use an experiment-driven approach to rapidly test hypotheses and refine prototypes in collaboration with client teams.

Develop reusable frameworks and tools to accelerate the deployment of generative AI solutions across diverse industries.

Cross-Functional Collaboration:

Work closely with Sales, Applied Research, Product Development, and Customer Success teams to ensure seamless project execution.

Provide actionable feedback from customer engagements to inform the development of new AI capabilities.

Knowledge Sharing:

Document best practices and lessons learned from client projects to contribute to internal knowledge bases.

Mentor junior engineers on the application of generative and agentic AI technologies in real-world scenarios.

Requirements

Technical Expertise:

Strong proficiency in programming languages such as Python or JavaScript, with experience in frameworks like TensorFlow or PyTorch.

Hands-on experience with generative AI models (e.g., GPT-4/5), agentic systems, or reinforcement learning frameworks.

Familiarity with deploying machine learning models in production environments using cloud platforms (e.g., AWS, Azure) or on-premise systems.

Problem-Solving Ability:

Proven ability to translate abstract business challenges into concrete technical solutions using generative AI.

Strong analytical skills to evaluate model performance and optimize for specific use cases.

Client-Facing Skills:

Exceptional communication skills for explaining complex AI concepts to diverse stakeholders.

Ability to build trust-based relationships with clients and navigate ambiguous problem domains collaboratively.

Adaptability:

Flexibility to work across industries such as healthcare, finance, defense, or retail while tailoring solutions to each domain.

Willingness to travel or work on-site with clients as required.

Requirements (Education, Certification, Training, and Experience)

Bachelor's degree in computer science or related field or equivalent experience

At least 3 years of experience in software engineering or applied machine learning roles.

Direct experience working with customers on the development of AI-driven applications is highly desirable

Passion for exploring the frontiers of generative and agentic AI technologies.

Entrepreneurial mindset with a focus on delivering measurable business impact through innovative solutions.

Commitment to continuous learning and staying at the forefront of AI advancements.

This role is ideal for those who thrive at the intersection of technology innovation and customer engagement. You will have the opportunity to shape the future of enterprise AI adoption while solving some of the most complex challenges faced by leading organizations.

ABOUT THE ROLE:

We are establishing a dedicated team of AI Engineers to serve as a long-term strategic AI partner to one of the most influential AI organizations in the Middle East, headquartered in the UAE. This team will work closely with a highly ambitious client operating at the forefront of AI adoption across the region, supporting a continuously evolving pipeline of AI-driven initiatives.

As an Senior AI Engineer, you will work directly with customer leadership, technical teams, and internal stakeholders to deeply understand complex use cases and design, build, and deploy impactful AI solutions. This role blends hands-on engineering, AI system design, and customer-facing strategy—similar in scope to a hands-on AI startup CTO.

Rather than supporting a single static product, you will work across multiple domains and initiatives as new opportunities emerge. The Middle East's strong national investment in AI creates a unique environment where experimentation, ambition, and real-world impact are expected, not optional.

WHAT MAKES THIS ROLE UNIQUE:

• A long-term strategic partnership, not short-term consulting
• Exposure to large-scale, high-impact AI initiatives across sectors such as government, healthcare, energy, smart cities, and advanced research
• The opportunity to design and deploy AI systems in an environment prioritizing speed, innovation, and real-world outcomes
• A high-trust, fast-moving setting where engineers have meaningful ownership and influence
  
  

• Partner closely with client stakeholders to understand strategic objectives, technical requirements, and operational constraints
• Act as a trusted advisor on AI strategy, helping customers identify, prioritize, and implement high-impact generative and agentic AI use cases
• Lead workshops, technical deep dives, and brainstorming sessions to translate business needs into AI-driven solutions
  
  

• Design, prototype, and deploy AI-powered proofs of concept (PoCs) and production solutions using generative AI models, agentic systems, and LLM workflows
• Build end-to-end AI pipelines, from data ingestion to deployment, ensuring scalability, security, and performance on modern infrastructure
• Implement solutions using the latest AI models and techniques, driving tangible business outcomes for the client
  
  

• Use an experiment-driven approach to rapidly test hypotheses, iterate on designs, and refine solutions in collaboration with client teams
• Explore and apply cutting-edge techniques in areas such as NLP, computer vision, reinforcement learning, and multi-agent systems
• Develop reusable frameworks, patterns, and tools to accelerate AI delivery across future initiatives
  
  

• Work closely with Sales, Solutions Engineering, Solutions Architects, Applied Research, Product, and Customer Success teams supporting the same account
• Provide structured feedback from customer engagements to influence internal product and platform development
  
  

• Document best practices, architectures, and lessons learned from deployments to strengthen internal delivery capabilities
• Mentor junior engineers on applying generative and agentic AI technologies in real-world, enterprise environments
  
  

• Strong proficiency in Python and/or JavaScript, with experience using ML frameworks such as PyTorch or TensorFlow
• Hands-on experience with generative AI models (e.g., GPT-4/5), LLM-based systems, agentic workflows, or reinforcement learning frameworks
• Experience deploying AI/ML systems into production using cloud platforms (AWS, Azure) or on-premise infrastructure
  
  

• Proven ability to translate ambiguous business challenges into concrete, scalable AI solutions
• Strong analytical skills to evaluate model performance and optimize systems for real-world constraints
  
  

• Excellent communication skills, with the ability to explain complex AI concepts to both technical and non-technical stakeholders
• Comfort operating in ambiguous, high-stakes environments while building trust-based client relationships
  
  

• Ability to work across multiple industries and domains, tailoring AI solutions to different contexts
• Entrepreneurial mindset with a focus on ownership, execution, and measurable impact
• Willingness to travel or work on-site with clients as required
  
  

• Bachelor's degree in Computer Science or a related field, or equivalent practical experience
• 3+ years of experience in software engineering, applied machine learning, or AI-focused roles
• Prior experience working directly with customers on AI-driven applications is highly desirable
• Passion for staying at the forefront of generative and agentic AI advancements and applying them pragmatically
  
  
  
  

Industry Insight

Transportation logistics is the foundational industry that powers everything we rely on daily, yet it remains a complex and fragmented domain ripe for technological revolution. The US transportation logistics industry alone is an $800 billion market.

Alvys is not just participating in this change; we are driving it as the fastest-growing Transportation Management System (TMS) in history, uniquely positioned to truly transform this essential sector.

Your role will be at the forefront of automating and standardizing a sector that moves trillions of dollars' worth of goods annually, predominantly by truck, but still lacks modern tools and solutions. Your leadership will help bridge this gap, bringing innovative technologies to a traditionally underserved and mission-critical industry.

About Alvys

Alvys is the fastest-growing Transportation Management System (TMS) in history, uniquely positioned to dominate and truly revolutionize the $800 billion US transportation logistics industry.

We're not just iterating on old tools; we're building a world-class, multi-tenant SaaS platform from the ground up to automate, standardize, and transform this essential sector. Join us to apply your technical vision to one of the economy's most mission-critical and underserved markets, making a massive, tangible impact on the movement of global goods.

This is where industry experience meets cutting-edge technology to create the undisputed market winner, and you will be a core part of that journey.

About The Role

As a Data Engineer, you will be the primary architect of our data ecosystem. Alvys is shifting toward a Snowflake-centric data architecture to power our next generation of logistics intelligence. You aren't just building pipelines; you are defining our LLM-based data strategy, enabling large-scale ML model deployment, and leveraging Snowflake Cortex to turn fragmented logistics data into actionable AI-driven products.

This is a high-visibility, 'player-coach' position. You will work closely with leadership to ensure our data infrastructure supports real-time operational needs today while scaling for the AI-first logistics world of 2026 and beyond.

Our Tech Stack

• Data Platform: Snowflake (Warehouse, Cortex AI/ML, Semantic Models, LLM Agents)
• Data Pipelines: dbt, Fivetran, Reverse ETL (Census)
• AI/ML: Snowflake Cortex, OpenAI, Azure Cognitive
• Backend/Infra: .NET/C#, Python, Azure Ecosystem, GitHub Actions

• Define and implement the strategy for LLM-based data products, including data preparation, semantic layer design, and embedding pipelines for RAG-based applications.
• Own the design and evolution of our Snowflake architecture. Lead the implementation of Snowflake Cortex for AI/ML workloads, including semantic models and LLM agents.
• Design and maintain reliable, performant ELT/Reverse ETL pipelines. Ensure our multi-tenant SaaS data remains isolated, secure, and performant at scale.
• Build and operationalize pipelines for large-scale ML and LLM model development, moving from POC to production-grade deployment within the Snowflake perimeter.
• Think holistically about the data estate. Reduce complexity through modularity and well-defined service boundaries (e.g., Medallion Architecture).
• Serve as the go-to expert for emerging data trends. Mentor engineers and partner with Product and Design to translate complex business logic into automated deliverables.

• 7+ years of experience in Data Engineering with a proven track record of delivering mission-critical data platforms.
• Deep proficiency in Snowflake (Data Modeling, Query Optimization, Security, and Cortex AI functions).
• Expert-level skill in SQL and Python. Extensive experience with dbt and modern orchestration (Airflow/Dagster).
• Demonstrated experience building pipelines for ML or LLM-based applications, including feature engineering and model deployment.
• Competency in Azure (preferred) or other major cloud providers, including CI/CD and infrastructure-as-code principles.
• Experience driving cross-team consensus on architectural decisions and mentoring junior/mid-level engineers.

• Ownership: You take end-to-end responsibility. If it’s in production, it’s yours—from the initial schema design to the final dashboard latency.
• Pragmatism: You believe technical debt is a strategic choice. You choose solutions that scale and solve real problems over theoretical "perfection."
• Simplicity: You prioritize modularity and clean design to reduce cognitive load in a complex logistics domain.
• Transparency: You democratize data. You ensure insights are accessible across the organization and participate in constructive feedback loops.

#LI-Hybrid