Job DescriptionExperience: 10+ Years (including ~2 years relevant agentic AI experience)
NLocation: Pune (In Office)
NExperience: 10+ Years (including ~2 years relevant agentic AI experience)
NSkills required
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- Agent & sub‐agent architecture N
- Ability to design multi‐agent systems with planners, workers, and specialized sub‐agents, including clear hand‐off protocols and failure‐handling. N
- Around 2 years of relevant experience building and operating agentic workflows in real projects or products. N

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- MCP servers and integrations N
- Hands‐on experience designing and implementing MCP servers that expose internal APIs, databases, and workflows to agents in a secure and observable way. N
- Practical knowledge of MCP client integration, transports (e.G., STDIO/HTTP), authentication/authorization, and managing connections to multiple MCP servers. N

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- Context management & data access N
- Solid understanding ofcontext engineering: chunking, summarization, windowing, and context isolation for long‐running or multi‐step agent flows. N




- Ability to choose and justify between MCP‐exposed tools, private data stores, and RAG/vector search for internal data, considering latency, security, and governance. N

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- Prompting,safety, and guardrails N
- Experience designing robust prompts for tools and agents, including patterns to mitigate prompt injection, prompt stuffing, and data‐exfiltration risks. N
- Familiarity with permissioned tools, human‐in‐the‐loop reviews, and policy checks before sensitive actions (e.G., code changes, production-impacting calls). N

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- Autonomousworkflows & Ralph loops N
- Experience setting up Ralph‐style or similar long‐running coding loops that iteratively modify codebases, gated by tests, linters, and explicit stop conditions. N
- Skills in observing, logging, and debugging agent runs (traces, run logs, metrics) and iterating on prompts/skills/MCP design based on real‐world feedback. N

📌 Ai Agent (India)
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