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DL

568505_Agentic AI+AWS

Diverse Lynx India
🇮🇳 India
On-site
3 weeks ago
  • AI
  • RAG
  • LangGraph
  • CrewAI
  • AutoGen
  • MCP
  • Model Context Protocol
  • AWS
  • GCP
  • Azure
3 weeks ago
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Description:
  • Explore & research: track the agentic AI landscape, evaluate new models, tools, and ideas, and run quick experiments to prove what is worth pursuing.
  • Develop AI agents: design and ship agents that reason, plan, use tools/APIs, and handle memory and retrieval (RAG).
  • Orchestrate multi-agent systems: build systems where specialized agents collaborate, delegate, and hand off tasks to solve complex problems.
  • Build with agent frameworks: implement agents using frameworks such as Strands, LangGraph, CrewAI, or AutoGen, applying the right patterns for each use case.
  • Implement MCP & integrations: connect agents to tools, data, and services through the Model Context Protocol (MCP) and other AI integration technologies and APIs.
  • Deploy on the cloud: package, deploy, and run agents on cloud platforms (AWS, GCP, or Azure) with scalability, security, and cost in mind.
  • Add observability: instrument agents with logging, tracing, and monitoring so behavior can be measured, debugged, and improved in production.
  • Productionize & evaluate: define quality, success, latency, and cost metrics, build eval harnesses, and optimize for reliability and scale.
  • Ensure safety: apply guardrails, tool permissions, and human-in-the-loop checks for responsible agent behavior.
  • Collaborate & enable : partner with product and domain teams, document decisions, and raise the team's overall agentic-AI fluency.

ECMS REQ ID
568505
Project Location 1
MAH | PUNE
Project Location 2
TELANGANA | HYDERABAD
Project Location 3
ORS | BHUBANESWAR
Project Location 4
(No Value)
Delivery SPOC
Relevant Experience
4+
Mandatory skills
• Explore & research: track the agentic AI landscape, evaluate new models, tools, and ideas, and run quick experiments to prove what is worth pursuing.
• Develop AI agents: design and ship agents that reason, plan, use tools/APIs, and handle memory and retrieval (RAG).
• Orchestrate multi-agent systems: build systems where specialized agents collaborate, delegate, and hand off tasks to solve complex problems.
• Build with agent frameworks: implement agents using frameworks such as Strands, LangGraph, CrewAI, or AutoGen, applying the right patterns for each use case.
• Implement MCP & integrations: connect agents to tools, data, and services through the Model Context Protocol (MCP) and other AI integration technologies and APIs.
• Deploy on the cloud: package, deploy, and run agents on cloud platforms (AWS, GCP, or Azure) with scalability, security, and cost in mind.
• Add observability: instrument agents with logging, tracing, and monitoring so behavior can be measured, debugged, and improved in production.
• Productionize & evaluate : Define quality, success, latency, and cost metrics, build eval harnesses, and optimize for reliability and scale.
• Ensure safety: apply guardrails, tool permissions, and human-in-the-loop checks for responsible agent behavior.
• Collaborate & enable: partner with product and domain teams, document decisions, and raise the team's overall agentic-AI fluency.

568505_Agentic AI+AWS · Diverse Lynx India

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