דרושים » הנדסה » Junior AI Agent Developer (copilot)

In one sentence
As AI reshapes the future of software, we aim to harness its power to transform the way networks, IT systems, and business operations are built and managed. We seek a visionary and hands-on AI Evangelist & Enablement Lead to join our company.
This is a unique hybrid role that combines deep technical expertise with a passion for teaching, enabling, and advocacy. As a member of the company agentic AI office. you will join our internal team of champions for AI-driving the adoption of Agentic and Generative AI across our company engineering and product teams, while also positioning our company as a thought leader in the global technology ecosystem.
What will your job look like?
Internal AI Enablement & Strategy
Partner with engineering and product development teams to integrate and optimize AI/GenAI tools throughout the software delivery lifecycle, from coding and testing to deployment and operations.
Define and champion best practices, coding standards, and standardized workflows for AI-assisted development across the organization.
Establish and lead an internal AI community of practice, fostering a culture of innovation, knowledge sharing, and responsible AI adoption.
Hands-on Implementation & Prototyping
Lead the evaluation, piloting, and integration of new AI development platforms (e.g., advanced coding assistants, MLOps frameworks, internal LLM deployments).
Build proof-of-concept projects and reusable AI components to showcase the value of emerging technologies and architectural patterns.
Design and document robust frameworks for leveraging AI services with a focus on scalability, performance, security, and cost-effectiveness.
Knowledge Sharing & Education
Create and deliver hands-on workshops, tech talks, and practical tutorials on topics like prompt engineering, AI-powered debugging, and integrating LLMs into production workflows.
Develop an internal knowledge base with code samples, case studies, and technical documentation to empower engineers to adopt and scale AI independently.
Mentor engineers and team leads, helping them grow their skills and confidence in applying AI to complex telecom and enterprise challenges.
External Evangelism & Thought Leadership
Represent our company as a technical expert at industry conferences, customer events, and developer communities.
Publish technical blog posts, whitepapers, and open-source contributions that showcase our companys innovative use of AI in the telecom and enterprise software domains.
Stay at the forefront of the rapidly evolving AI landscape, bringing back insights and opportunities to the organization.

We are seeking an experienced Generative AI Engineer to join our AI squad at our company. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities
GenAI Development & Implementation
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment.