Software AI Engineer Mid-Level, Context Engineering

Responsibilities

• Feature Development : Implement and maintain core services for the AI Data Lakehouse, focusing on efficient data retrieval and storage optimizations for AI workflows.
• Pipeline Automation : Build and support CI/CD pipelines to automate the deployment of AI models, prompt templates, and infrastructure updates.
• Agentic Support : Develop and test tool-execution environments and API interfaces that allow AI agents to interact with internal business systems safely.
• Operational Excellence : Participate in on-call rotations and troubleshooting to ensure platform reliability. Write unit tests, integration tests, and documentation for new features.
• Context Retrieval : Work on the "Context Fabric" to implement search and retrieval patterns (like RAG) that help agents access secure enterprise data.
• Cloud Management : Assist in managing cloud resources across AWS and Azure, ensuring environments are cost-effective and secure.
• Qualifications & Experience
• Software Engineering Foundation
• Experience : 3+ years of professional software development experience.
• Core Skills : Strong proficiency in Python and either Java or Scala . You write clean, maintainable, and well-documented code.
• API Development : Experience building and consuming RESTful APIs or gRPC services.
• Database Basics : Understanding of relational databases (Postgres/MySQL) and familiarity with how data is stored in a distributed environment.
• Cloud & CI/CD Mastery
• Cloud Consoles : Hands-on experience navigating the AWS or Azure Management Consoles . You should be comfortable managing basic services like IAM, S3/Blob, and compute instances.
• Infrastructure-as-Code (IaC) : Basic experience with Terraform . You can read, modify, and deploy infrastructure modules.
• CI/CD Tools : Familiarity with GitHub Actions, GitLab CI, or Jenkins. You understand how to automate the build-test-deploy lifecycle.
• Observability : Basic experience with monitoring tools like Prometheus, Grafana, or cloud-native solutions (CloudWatch/Azure Monitor).
• AI & Agentic Interests (Specialized Focus)
• LLM Awareness : Familiarity with LLM concepts and frameworks like LangChain or LlamaIndex . You've experimented with or built basic RAG-based applications.
• Emerging Protocols : A desire to learn and implement new standards like the Model Context Protocol (MCP) .
• Agentic Workflows : Interest in how autonomous agents function, including tool-use (function calling) and state management.
• Data Retrieval : Basic understanding of vector databases (e.g., Pinecone, Milvus) and how search impacts AI performance.
• Leadership & Education
• Team Player : Ability to work effectively in an agile environment, participating in sprint planning and daily stand-ups.
• Continuous Learner : A strong desire to stay current with the rapidly changing AI and cloud landscape.
• Education : Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• Pay Range: $124,700.00 - $148,800.00

Benefits

Additional Information

As an AI Platform Engineer (SDE 2) , you will be a hands-on developer responsible for building and maintaining the core software components that power our AI and context infrastructure. You will work on the "Context Layer"-the plumbing that connects enterprise data to LLMs-ensuring that our AI agents have the right information at the right time. This role is ideal for a strong software engineer who wants to specialize in the operational side of AI, focusing on high-quality code, automated delivery, and cloud-native systems.

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