AI Software Developer

About the Company:

We are recruiting on behalf of a leading technology and digital infrastructure organization supporting telecommunications and large enterprise environments .

The organization works on complex digital infrastructure and enterprise technology solutions, with a strong focus on cloud-native software, AI, automation, and modern application architectures .

The team is building practical AI solutions that move beyond experimentation — taking ideas from technical discovery and proof of concept through MVP, production deployment, and ongoing optimization .

The Role:

We are looking for a hands-on AI Software Developer who combines strong enterprise software engineering experience with practical experience building and deploying AI systems.

This role is ideal for an engineer who enjoys working at the intersection of software engineering, generative AI, cloud platforms, and agentic systems .

You will work closely with data engineers, platform engineers, architects, and business stakeholders to translate business requirements into reliable production software.

The ideal candidate should have experience taking AI solutions from PoC to production and should be able to clearly explain at least two AI/software solutions they have personally helped deliver to production , including their specific contribution.

What You Will Do:

• Build AI-Powered Applications: Develop production applications using generative AI, foundation models, APIs, AI frameworks, and cloud services.
• Develop Agentic Systems: Design and implement agentic applications involving tool use, multi-step workflows, research patterns, automation, and intelligent decision-making .
• Build Cloud-Native Software: Develop scalable applications using microservices, event-driven architectures, APIs, and modern cloud-native engineering practices .
• Integrate AI Technologies: Evaluate and integrate appropriate foundation models, AI frameworks, APIs, and cloud services based on specific business and technical requirements.
• Take Solutions to Production: Own solutions through the full development lifecycle — from technical discovery and proof of concept to MVP, deployment, and ongoing production use .
• Make Architecture Decisions: Make engineering and architecture decisions that balance reliability, scalability, security, performance, cost, and maintainability .
• Translate Business Requirements: Work with technical and nontechnical stakeholders to understand business problems and turn them into practical, working software solutions.
• Technical Discovery: Participate in early-stage technical discovery, help define solution approaches, identify technical considerations, and shape architecture before development begins.
• Cross-Functional Collaboration: Partner with data engineers, platform engineers, architects, and other technical teams to deliver enterprise-grade AI solutions.
• Communicate Technical Trade-offs: Clearly explain architectural decisions, technical trade-offs, limitations, risks, and recommended approaches to both technical and business stakeholders.

What We Are Looking For:

• Enterprise Software Engineering Experience: 7–10 years of professional enterprise software development experience with strong software engineering fundamentals.
• Hands-On AI Development: At least 3 years of hands-on AI development experience , preferably involving production AI systems.
• Production AI Experience: Direct involvement in delivering at least two AI/software solutions into production , with the ability to explain your personal contribution to each.
• Strong Software Architecture: Solid understanding of software architecture, application design, scalability, maintainability, and engineering best practices.
• Cloud Experience: Hands-on experience with at least one major cloud platform such as Azure, AWS, or GCP .
• Foundation Models: Experience working with foundation models such as GPT, Claude, Llama, or equivalent models .
• Agentic AI: Practical experience designing and developing agentic applications, AI agents, tool-calling systems, and multi-step AI workflows .
• Modern Application Architecture: Strong understanding of **APIs, microservices, event-driven architectures, and cloud-native application d…