AI Data Engineer

Job Description

• Proven experience as a Software Engineer with strong proficiency in Python and/or Java, writing clean, scalable, production-grade code.
• Solid experience designing and building microservices and RESTful APIs in distributed, cloud-based environments.
• Experience designing, implementing, and extending AI agentic systems, including tool use, planning, and autonomous decision-making workflows.
• Experience building multi-agent systems where multiple agents collaborate, delegate, and coordinate to complete complex tasks.
• Hands-on experience building conversational or chat systems with both short-term (session) and long-term (persistent) context management.
• Experience building Retrieval-Augmented Generation (RAG) systems, including document ingestion, chunking strategies, vector stores, and retrieval pipelines.
• Experience building MCP servers.
• Experience integrating agentic systems with external APIs, third-party services, and enterprise data sources.
• Strong understanding of security in agentic systems, including authentication, authorization, least-privilege access, prompt injection defense, and audit logging.
• Knowledge of relational databases such as PostgreSQL and Microsoft SQL Server.
• Knowledge of vector databases such as Qdrant, Pinecone, pgvector, and Weaviate.
• Experience using system and performance monitoring tools, such as New Relic and Datadog.
• Proficient in Git and comfortable working in CI/CD-driven development workflows.
• Excellent critical-thinking, communication, and personal leadership skills.
• Self-starter with the ability to deliver with minimal supervision.
• BSc/BA in Computer Science or a related degree.

Bonus Points

• Experience with distributed computing.
• Experience writing code/scripts in Python.
• Experience with Spring Boot.
• Nice to have: React, Selenium automation, and cloud experience.
• Nice to have: Document parsing systems, including extraction from PDFs, structured/unstructured data sources, and handling diverse file formats.
• Experience with Docker, Kubernetes, and Istio.
• Experience with Ansible.
• Experience with CI/CD pipelines using Spinnaker and/or GitHub Actions.
• Knowledge of Linux and IP networking.
• Experience with AWS/Azure cloud services or equivalent.
• Experience with Terraform for infrastructure as code and cloud provisioning.
• Nice to have: Experience with SAML, OAuth, and OpenID Connect.
• Experience working on a SaaS product.
• Experience with Service-Oriented Architecture (SOA).
• On-call experience with production-grade systems.
• Experience mentoring others in a professional setting.
• Experience using Generative AI Code Assistants, such as GitHub Copilot, and knowledge of the latest Generative AI model capabilities.