Software Engineer (Infrastructure)

Experience

• 5+ years of experience in backend or infrastructure engineering, ideally supporting production AI/ML systems or high-throughput data pipelines.
• Proven track record of building and scaling infrastructure in production environments.

Technical Skills

• Proficiency in Python.
• Databases: Proficiency in SQL (PostgreSQL, MySQL) and NoSQL (e.g. Document DB, Vector DB).
• Cloud: Deep experience deploying and scaling large production applications on AWS, GCP, or Azure.
• Containerization and orchestration: Docker, Kubernetes.
• Security: Strong understanding of OAuth2, JWT, and best practices for securing distributed systems.

• Experience with RPA (Robotic Process Automation) tools.
• Familiarity with graph databases (Neo4j) for managing complex workflows.
• Familiarity with Go and Rust.
• Experience working alongside AI/ML teams using frameworks like TensorFlow, PyTorch, or Hugging Face.

• Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.
• Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

• Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.
• Own containerization and orchestration (Docker, Kubernetes) for all production workloads.
• Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

• Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.
• Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

• Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.
• Design for reliability: retries, observability, and graceful degradation across distributed systems.

• Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.
• Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

• Build observability and monitoring systems to track infrastructure health, performance, and cost.
• Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

• Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.
• Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact.