Sr Analyst III: AI Systems Engineer - Storage & Backup

Job Description:

·         Develop Python-based components for OASIS storage/backup integrations — including individual MCP tools, vendor REST API integrations, and Pydantic data models — under the direction of senior team members.

·         Write, test, and debug code for assigned features within the team’s agents, MCP tool servers, and FastAPI services.

·         Collaborate with team members to meet project goals, taking direction from senior team members on architectural and design decisions.

·         Participate in design discussions and code reviews; submit pull requests with appropriate test coverage, changelog entries, and version increments per team conventions.

·         Participate in troubleshooting and resolving technical issues across the agent → MCP server → vendor API stack, under the guidance of senior engineers.

·         Use structured logging and OpenTelemetry traces to support troubleshooting and incident analysis.

·         Learn and apply agentic AI patterns (LLM tool calling, ReAct graphs, RAG, prompt engineering) to assigned work; build proficiency with the OASIS SDK ecosystem and team coding standards.

·         Stay updated on emerging technologies and best practices; seek opportunities for professional development.

·         Contribute to knowledge sharing, onboarding documentation, and team learning as you ramp.

·         Use Claude Code (or comparable AI coding assistants) as a routine part of the development and documentation workflow.

·         Bachelor’s degree in Computer Science or equivalent combination of education and experience.

·         Typically 3+ years of relevant software engineering experience, with at least 1 year in a similar backend, API, or software development role.

·         Working proficiency in Python, including async/await patterns, type hints, and virtual environments.

·         Working knowledge of REST APIs, JSON, and HTTP fundamentals.

·         Proficient with Git and Git-based code review workflows on GitHub or GitHub Enterprise.

·         Comfortable working in a Linux / WSL terminal and writing or modifying bash scripts.

·         General awareness of AI/LLM concepts (prompt engineering, tool calling) — direct exposure is a plus; willingness to learn is required.

·         Solid coding and debugging skills with eagerness to grow.

·         Effective communication and collaboration abilities.

·         Willingness to learn and gain practical experience in a complex multi-service stack.

·         Hands-on experience with FastAPI, Pydantic, async programming, or REST API integration is a plus.

·         Exposure to agent frameworks (LangGraph, LangChain) or agent integration standards (MCP, A2A) is a plus.

·         Exposure to AWS (especially Bedrock), OpenTelemetry, or structured logging is a plus.

·         Familiarity with enterprise storage or backup concepts (volumes, snapshots, replication, backups) is a plus.

·         Advanced degree in a related field is a plus.

·         Relevant certifications or training are a plus.

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