Senior Artificial Intelligence Engineer

• This role is ideal for someone passionate about enabling AI innovation through robust infrastructure, intuitive tooling, and seamless integration of cutting-edge models.
• You’ll be at the forefront of operationalizing AI—designing systems that empower teams to build, deploy, and iterate on intelligent applications with speed and reliability
• Platform Architecture & Development:
  Design and implement scalable AI platforms using Python. Integrate MLOps tools for model versioning, deployment, monitoring, and lifecycle management
• AI Tooling & LLM Capabilities:
  Build tools and abstractions to interface with large language models, including prompting frameworks, agentic workflows (e.g., with Lang Graph), and LLM orchestration services
• Data Engineering & ETL:
  Collaborate with data teams to build robust ETL pipelines, preprocess training data, and construct feature workflows that feed AI models at scale
• Reliability & Monitoring:
  Implement model monitoring dashboards to ensure platform reliability and performance, and investigate production prompt results
• Research & Innovation:
  Stay ahead of cutting-edge trends in Generative AI. Prototype AI scenarios that unlock new product or operational value
• Testing, Documentation & Standards:
  Define rigorous unit, integration, and performance testing methodologies. Maintain comprehensive documentation and enforce best practices for ethical and secure AI usage

• Premium Health Benefits
• Distributed Team Building
• Learning & Development
• Award Winning Culture

Solid understanding of MLOps principles: CI/CD, model versioning, monitoring, metrics

Familiarity with LLM prompting design, agentic workflows (e.g. Lang Graph)
Nice to Have Exceptional communication and collaboration across engineering and product teams

Bachelor’s or Master’s in Computer Science, Engineering, or related field

Awareness of AI ethics, biases, fairness, and data privacy protocols4+ years of experience building production-grade AI/ML platforms or developer-centric AI tools

Experience with large-scale data pipelines (e.g., Apache Spark, Kafka)
Certifications in cloud platforms, ML engineering, or specific AI tooling

Strong software engineering skills in Python (preferred) and familiarity with Java/Go and OOP/data structures

Experience building and deploying on cloud platforms (AWS, Google Cloud, Azure); familiar with Docker and Kubernetes