AI Engineering Lead

Description

Job id 5408

Why Ness

We know that people are our greatest asset. Our staff’s professionalism, innovation, teamwork, and dedication to excellence have helped us become one of the world’s leading technology companies. It is these qualities that are vital to our continued success. As a Ness employee, you will be working on products and platforms for some of the most innovative software companies in the world.

You’ll gain knowledge working alongside other highly skilled professionals that will help accelerate your career progression.

You’ll also benefit from an array of advantages like access to trainings and certifications, bonuses, and aids, socializing activities, and attractive compensation.

Requirements and responsibilities

The Lead AI Engineer will be responsible for defining the technical vision, architecture, and implementation strategy for AI-powered capabilities. This role requires a strong mix of hands-on technical expertise, architectural leadership, and strategic thinking to ensure the development of a scalable, secure, and high-performance AI-driven platform. The AI Tech Lead will work closely with product management, UX, and engineering teams to translate business requirements into a robust technical solution that enhances user experience, streamlines data integration, and enables AI-driven insights.

What you'll do

Technical Strategy & Architecture

• Develop a scalable and modular AI architecture that integrates seamlessly with existing customer platforms.
  
• Define and implement best practices for AI model deployment, data processing, and cloud infrastructure.
  
• Establish a clear roadmap for AI-driven capabilities, ensuring alignment with business goals.
  

AI & Data Engineering

• Design and implement Retrieval-Augmented Generation (RAG) pipelines and AI-driven data processing workflows.
  
• Design and develop complex agent-based solutions.
  
• Develop and optimize AI models tailored to enhance automation, personalization, and insights for client users.
  
• Ensure the integration of structured and unstructured data sources into AI workflows.
  
• Establish data governance frameworks, security models, and compliance strategies for AI usage.
  

Solution Development & Implementation Planning

• Collaborate with UX and product teams to define AI-powered user experience improvements.
  
• Identify and implement technical accelerators to optimize development speed and platform efficiency.
  
• Define technical milestones, effort estimations, and cost evaluations for implementation.
  

Collaboration & Stakeholder Management

• Work closely with product managers, designers, and engineers to align technical solutions with business needs.
  
• Provide technical leadership to engineering teams, guiding them in AI model deployment and system scalability.
  
• Engage with stakeholders to validate architectural decisions and refine technical requirements.
  

Performance Optimization & Scalability

• Establish monitoring frameworks for AI model performance, system reliability, and infrastructure scalability.
  
• Optimize AI pipelines and data processing layers to ensure real-time insights and efficient workflows.
  
• Address system bottlenecks and propose enhancements to improve user experience and cross-platform integrations.
  

What you'll bring

Technical Expertise

• Proven experience as an AI Tech Lead or ML Engineer, ideally in customer-facing, production-deployed projects.
  
• Solid understanding of deep learning concepts, supervised / unsupervised / self-supervised / reinforcement learning.
  
• Solid understanding of Large Language Models, Transformers architecture, self-attention, mixture of experts, and embedding models.
  
• Proven experience with advanced Retrieval Augmented Generation, vector DBs, and prompt engineering.
  
• Expertise with AI agents design, orchestration and optimisation.
  
• Experience with CrewAI, LangChain / LangSmith / LangGraph, and/or LlamaIndex.
  
• Experience with model fine-tuning.
  
• Hands-on data pre-processing experience.
  
• Strong Python expertise.
  
• Proficiency in ML frameworks such as PyTorch, TensorFlow, or similar.
  
• Experience with AWS development and deployment (ECS, Lambda, S3).
  
• Experience with at least one of the following cloud-based AI platforms (preferrably AWS): AWS SageMaker / AWS Bedrock / Azure ML.
  
• LLMOps expertise.
  
• Familiarity with Docker and Kubernetes.
  

Leadership & Communication

• Strong ability to translate technical concepts into business-impact discussions.
  
• Experience leading AI engineering teams and working in cross-functional environments.
  
• Track record of working with product and business teams to define AI-driven solutions.
  

Strategic & Problem-Solving Skills

• Ability to assess existing systems, identify gaps, and develop AI-driven enhancements.
  
• Experience in defining and implementing AI strategies for enterprise-grade products.
  
• Strong analytical mindset with a focus on performance optimization and data-driven decision-making.

Not checking every single requirement?

If this role sounds good to you, even if you don’t meet every single bullet point in the job description, we encourage you to apply anyway. For most of the candidates that applied, we found a role that was a very good fit with their skills.

Let’s meet and you may just be the right candidate for one of our roles.

At Ness Digital Engineering we are willing to build a work culture that is based on diversification, inclusion, and authenticity.