Works directly with LLMs, agent orchestration, and prompt engineering—very much in the vibe-coding space focused on agent-driven AI and prompt/tooling optimization.
About the Role
Senior AI professional role to design, develop, and optimize production-grade agentic AI solutions for telecommunications, focusing on turning AI concepts into reliable, scalable software. The role emphasizes prompt optimization, model behavior, agent orchestration, evaluation, and collaboration with platform engineers and product teams to improve AI quality and performance in production.
Job Description
Role
Design, develop, and optimize production-grade agentic AI solutions that prioritize reliability, scalability, and production readiness rather than pure research. Collaborate with platform engineers, product teams, and business stakeholders to improve AI quality, reliability, and performance.
Key Responsibilities
- Design, develop, and optimize agentic AI solutions for production.
- Run meaningful evaluations to improve prompts, model behavior, orchestration, reliability, and performance.
- Implement and maintain production-level AI/ML services, APIs, data pipelines, and backend integrations.
- Measure and improve AI quality, reliability, and performance in production environments.
- Collaborate with platform engineering, product teams, and stakeholders to deliver maintainable, production-quality solutions.
Requirements
- Deep expertise in machine learning and applied AI.
- Experience building and deploying production-level AI/ML services.
- Strong software engineering and coding skills.
- Experience developing or optimizing LLM- and agent-based applications.
- Strong knowledge of prompt engineering and optimization.
- Strong knowledge of model evaluation, benchmarking, and performance measurement.
- Familiarity with APIs, data pipelines, backend systems, and AI platforms.
- Familiarity with modern AI tools, frameworks, and cloud environments.
- Ability to design and run meaningful evaluations and interpret results.
- Strong communication skills and experience delivering maintainable, production-quality solutions.
Nice to Have
- Python experience.
- Background as an Applied AI Scientist, AI Engineer, or Machine Learning Engineer.
Engagement Highlights
- Own a defined production AI workstream with direct impact on reliability and scale.
- Work closely with an existing platform engineering team on applied AI delivery.
- Focus on production-grade AI implementation rather than purely research-oriented work.