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 development
.
Architecture Decision-Making:
Ability to evaluate different technical approaches and make architecture decisions based on
performance, reliability, scalability, security, cost, and maintainability
.
Communication Skills:
Strong ability to communicate technical concepts and trade-offs to both
technical and nontechnical stakeholders
.
Preferred Background:
Experience in
telecommunications, digital network infrastructure, or large enterprise technology environments
would be highly valuable.
Additional relevant experience includes
Enterprise SaaS development
AI evaluation and testing
AI observability and monitoring
AI security and governance
Technical discovery
Solution architecture
Pre-sales or customer-facing technical consulting
Cloud certifications
AI/ML certifications
Why This Role?
This is an opportunity for an experienced software engineer to work on
real-world AI systems that are designed for production
, rather than purely experimental or research-focused applications.
You will have the opportunity to work across
generative AI, foundation models, agentic workflows, cloud-native architecture, microservices, and enterprise software development
, while helping take solutions from early technical discovery all the way into production.
The role offers the opportunity to work alongside
data engineers, platform engineers, architects, and business stakeholders
and play a direct role in shaping how AI is applied to complex telecommunications and enterprise digital infrastructure environments.