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# Azure OpenAI Engineer

- **Company:** OpenKyber LLC
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $166,400.0 - $208,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Python (Programming Language), Machine Learning, OpenAI, Tensorflow, Software Engineering, User-Centered Design, Data Ingestion, Pytorch, Delivery Pipeline, Large Language Models, Prompt Engineering, Generative AI, Agentic-AI, AI Platforms, Scikit Learn, Information Technology, Machine Learning Operations, Drift Detection, Software Version Control
- **Published:** October 15, 2026
- **Apply:** https://www.careerjet.com/jobad/us64c913c27322ba8ca3be85f0bc00b6c7

## About the Role

8+ years of software engineering experience with 4+ years in AI/ML. Proven experience in a Tech Lead or senior technical role. Strong Python programming skills. Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn. Experience with cloud platforms (AWS, Azure, or GCP).
Nice to Have; Preferred Qualifications
Experience with Generative AI, LLMs, and agent-based systems. Knowledge of AI ethics, explainability, and bias mitigation. Master"s degree or higher in Computer Science, AI, or related fields.
Soft Skills
Strong technical leadership and ownership mindset. Excellent communication and stakeholder management skills. Passion for mentoring and team development.

## Description

We are looking for an experienced AI Engineer Tech Lead to lead the design, development, and deployment of scalable AI/ML and Generative AI solutions. This role combines deep technical expertise with strong technical leadership, guiding teams to build production-grade AI systems that deliver measurable business impact.
Day to Day job Duties: (what this person will do on a daily/weekly basis)

 * Lead end-to-end design and implementation of AI/ML and Generative AI solutions.
 * Own AI system architecture including model lifecycle, pipelines, and inference services.
 * Review code, models, and architectures to ensure quality, scalability, performance, and security.
 * Mentor and guide AI engineers and data scientists.
 * Define engineering best practices and MLOps standards.

AI & ML Engineering Responsibilities

 * Design, train, fine-tune, and deploy ML, DL, and LLM-based models.
 * Build pipelines for data ingestion, preprocessing, training, and evaluation.
 * Implement prompt engineering, RAG pipelines, and agentic workflows.
 * Optimize models for accuracy, latency, and cost.

System Design & Architecture

 * Architect cloud-native, scalable AI solutions.
 * Integrate AI systems with enterprise platforms, APIs, and data sources.
 * Ensure security, privacy, compliance, and governance requirements are met.

MLOps & Production Readiness

 * Lead CI/CD for ML systems.
 * Implement model versioning, monitoring, and drift detection.
 * Drive observability and reliability of AI services.