Senior AI Engineer
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Senior AI Engineer
2,00,000–18,00,000 / Year
Location
Mumbai, Maharashtra, India
Experience
Senior
Posted
Jul 7, 2026
Apply by
August 6, 2026
Applicants
0
Early applicantFull-timeWork from Office
Job Description
**This role is for one of the Weekday's clients**
**Salary range: Rs 200000 - Rs 1800000 (ie INR 2-18 LPA)**
Min Experience: 2+ years
Location: Mumbai
JobType: full-time
We are looking for a hands-on, deeply passionate Agentic AI Engineer who will help us turn cutting-edge Agentic AI and Multi-agent Systems into real-world value by designing, developing, and deploying intelligent agent solutions that run seamlessly on our clients’ existing infrastructure — while also powering our own internal product offerings.
Key Responsibilities
•Design, build, and optimize Multi-agent Systems and Agentic AI architectures that deliver measurable business outcomes.
•Develop agentic workflows to automate complex, multi-step processes across domains (finance, operations, customer support, data engineering, etc.).
•Architect and implement production-grade Agentic AI services that clients can deploy on their own infrastructure (on-prem, private cloud, or hybrid).
•Lead the deployment of MCP servers and related agent orchestration layers on multiple cloud and data platforms, with deep expertise in Azure and Databricks.
•Integrate agents with existing enterprise systems, data lakes, APIs, and security frameworks without requiring clients to rip-and-replace their stack.
•Continuously evaluate and integrate the latest Agentic AI frameworks, memory systems, tool-use patterns, and reasoning engines (ReAct, Plan-and-Execute, multi-agent collaboration protocols, etc.).
•Collaborate with client engineering teams to co-create and productionize custom agents that operate securely within their environments.
Required Qualifications & Experience
•Proven track record of developing agentic workflows that automate end-to-end business processes.
•Strong experience with deployment of MCP servers and agent orchestration platforms.
•Experience deploying Agentic AI solutions across multiple platforms (Azure, AWS, GCP, on-prem, Kubernetes) and making them work reliably in client-controlled environments.
•Solid understanding of MLOps, CI/CD for AI, monitoring
### Must-have skills
Agentic AI, Multi-agent Systems, MCP servers
### Good-to-have skills
CI/CD, MLOps, LLM
Key Responsibilities
- Design, build, and optimize Multi-agent Systems and Agentic AI architectures.
- Develop agentic workflows to automate complex, multi-step processes across domains.
- Architect and implement production-grade Agentic AI services for client deployment.
- Lead deployment of MCP servers and agent orchestration layers on cloud and data platforms.
- Integrate agents with existing enterprise systems, data lakes, APIs, and security frameworks.
- Evaluate and integrate latest Agentic AI frameworks, memory systems, and reasoning engines.
- Collaborate with client engineering teams to co-create and productionize custom agents.
Skills Required
Agentic AIMulti-agent SystemsMCP serversAzureDatabricksKubernetesAWSGCPMLOpsCI/CDLLMCollaborationProblem solving
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