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Bengaluru, Karnataka, India
Onsite
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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