- Company Name
- HyperAgentic.Ai
- Job Title
- Senior AI Engineer
- Job Description
-
**Job title**: Senior AI Engineer
**Role Summary**: Lead the design, implementation, and optimization of core AI agents and automation frameworks, driving innovation in distributed AI systems to deliver scalable, intelligent solutions.
**Expactations**:
- Architect and build next‑generation AI agents at a cutting‑edge enterprise automation firm.
- Collaborate with cross‑functional teams to translate business needs into robust AI architectures.
- Mentor and guide a team of AI/ML engineers, fostering best practices in code quality, testing, and performance.
- Maintain high standards for reproducibility, scalability, and security across distributed environments.
- Stay current with advancements in machine learning, distributed systems, and relevant programming languages.
**Key Responsibilities**:
- Design and develop AI agent pipelines using Python, Go, or Rust.
- Engineer scalable distributed systems that support real‑time inference and large‑scale data processing.
- Lead code reviews, enforce software engineering standards, and ensure rigorous testing frameworks are in place.
- Optimize performance and resource utilization through profiling, tuning, and efficient algorithm design.
- Integrate AI models with deployment platforms, monitoring, and observability tools.
- Collaborate with product and data teams to refine requirements, define success metrics, and iterate on solutions.
**Required Skills**:
- Proficiency in Python; strong command of Go or Rust (choose at least one).
- Demonstrated experience building end‑to‑end machine learning pipelines and AI systems.
- Deep understanding of distributed computing concepts, including cluster orchestration, fault tolerance, and data consistency.
- Expertise in version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes).
- Strong debugging, profiling, and performance‑tuning abilities.
- Excellent communication skills in English, with the ability to explain technical concepts to non‑technical stakeholders.
**Required Education & Certifications**:
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or a related technical field (or equivalent professional experience).
- No specific certifications required; knowledge of AI/ML and distributed systems certifications (e.g., AWS Certified Machine Learning, Kubernetes Administrator) is a plus.