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# AI Engineer

- **Company:** HEXA CONSULTING CORP.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Java (Programming Language), Artificial Intelligence, Machine Learning, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Agentic-AI, Pyspark, Information Technology, Virtual Agents
- **Published:** November 3, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pwo6u15nrz

## About the Role

Academic background at Master's level in Data Science, Statistics, Computer Science or a related field.

 - At least 3 years of experience in Machine Learning, Generative AI or related AI engineering contexts.

 - Strong knowledge of modeling, optimization and LLM-based solutions.

 - Experience designing and evaluating RAG, embeddings and AI monitoring approaches.

 - Ability to lead technical discussions, guide junior profiles and communicate clearly with technical and business stakeholders.

 - Strong analytical mindset, ownership and focus on quality, robustness and scalable delivery.

TECHNICAL SKILLS

 - Machine Learning

 - Generative AI

 - Large Language Models

 - RAG pipelines

 - Embeddings

 - Prompt engineering

 - Model evaluation

 - AI monitoring

 - Python

 - Spark

 - Java

 - LangChain

 - LangGraph or similar agentic frameworks

## Description

We are looking for a AI Engineer to lead the design and development of Machine Learning, Generative AI and agentic solutions in the telecommunications sector, in a hybrid work model. This role covers the end-to-end lifecycle, from business problem analysis to deployment, monitoring and continuous improvement.

WHAT YOU WILL DO

 - Lead the design of Machine Learning, Generative AI, RAG and AI agent use cases with business impact.

 - Translate complex business needs into analytical and AI-based solutions.

 - Define technical approaches involving Machine Learning, LLMs, prompt engineering, embeddings and agentic frameworks.

 - Contribute across the full solution lifecycle, from problem framing and experimentation to deployment and monitoring.

 - Define evaluation frameworks for models, outputs, performance and solution reliability.

 - Support the optimization, robustness and scalability of AI solutions.

 - Mentor junior Data Scientists and contribute to technical knowledge sharing within the team.