Software Development Engineer - AI Platform

Implement AI Platforms: Develop and maintain sophisticated AI platform capabilities, focusing on patterns like tool calling, multi-agent architectures, and human-in-the-loop integrations. You will write clean, performant code that ensures these systems are resilient in production.

Build ML Infrastructure: Develop and deploy secure, RESTful web services using Python and Kubernetes. You will contribute to the development of multi-tenant runtime architectures that enable fast inference and scale to millions of users.

Collaborative Engineering: Participate in design reviews and code quality initiatives. You will apply software development best practices to ensure our codebase remains maintainable, testable, and efficient.

Translate Requirements: Work with cross-functional teams to turn product requirements into functional technical designs.

Apply MLOps Standards: Utilize industry-standard practices, including automation, observability, and CI/CD, to deliver high-quality ML solutions.

Continuous Learning: Stay current with evolving AI/ML technologies and contribute to the team’s collective knowledge.

5+ years experience in software development engineering including designing, developing, and deploying software solutions.

2+ years of experience in Python, with a consistent track record of shipping production code and systems.

2+ of experience building scalable data pipelines and working with large-scale datasets.

2+ years of validated experience deploying production services to cloud platforms (e.g., AWS, Azure, GCP) and using containerization technologies (e.g., Docker, Kubernetes) for MLOps.

Bachelor’s degree in a relevant field such as Computer Science, Engineering, or a related discipline, or equivalent practical experience.

Solid ability in Algorithmic Thinking to design and implement efficient solutions for agentic system development.

Expertise in the engineering, deployment, and MLOps of advanced machine learning solutions (e.g., generative models, LLMs, RAG, and AI agents), coupled with a strong understanding of scalable distributed systems, performance optimization, database technologies (e.g., Postgre

SQL, Redis), and robust API development.

Validated algorithmic thinking and a track proven history designing, implementing, and analyzing efficient algorithms for complex problems.

Demonstrated ability to build flexible, reusable, and well-documented software components, with comprehensive experience in code testing strategies (unit, integration, end-to-end) in a continuous deployment environment. Strong sense of ownership and a proven ability to deliver high-quality, finished products efficiently.

Excellent communication and collaboration skills, emphasizing team collaboration, knowledge-sharing, and delivering customer impact.