Python Engineer _ Agentic AI & MCP Orchestration

Must Have Technical/Functional Skills

Technical Skills

* Strong hands-on experience in Python for building production-grade applications.

* Experience developing agentic AI applications (multi-agent workflows, tool-using agents, autonomous task execution).

* Expertise with AI orchestration frameworks (agents, tools, planners, workflow controllers).

* Practical experience setting up and configuring Model Context Protocol (MCP) servers.

* Ability to implement and integrate MCP Clients with external systems and AI models.

* Proficiency working with LLMs, prompt engineering patterns, and structured output handling.

* Experience with API integration, event-driven interactions, and tool/skill registration for agents.

* Strong understanding of asynchronous Python (asyncio, concurrency patterns).

* Familiarity with vector stores, embeddings, RAG pipelines, and memory architectures (nice to have).

* Experience working with CI/CD, Git, testing frameworks (pytest), and secure coding practices.

Functional Skills

* Ability to translate business problems into agent-driven automation workflows.

* Strong debugging and troubleshooting of distributed agent behavior and orchestration flows.

* Familiarity with governance, model safety constraints, and responsible AI usage patterns.

* Strong documentation habits for API schemas, MCP interface definitions, and agent lifecycle behavior.

* Effective communication with architects, product teams, and business stakeholders.

* Comfort working in Agile environments with rapid experimentation and iteration.

Roles Responsibilities

Design and develop Python-based agentic applications capable of orchestrating autonomous and semi-autonomous workflows.

* Build, configure, and maintain MCP servers to expose tools, data sources, or domain capabilities to LLM agents.

* Implement and configure MCP clients to interact with multiple MCP tools, AI models, and external systems.

* Develop orchestration logic to coordinate multi-agent behaviors, tool execution, validations, and decision routing.

* Integrate LLMs with internal systems using structured prompts, tool definitions, and safe execution patterns.

* Optimize agent workflows for reliability, performance, security, and cost.

* Create reusable frameworks for agent tools, context handling, memory, and reasoning cycles.

* Collaborate with architecture, platform, and product teams to align on engineering best practices.

* Implement observability: logging, tracing, and monitoring of agent reasoning steps and tool calls.

* Document MCP schemas, agent behaviors, tool interfaces, and operability guidelines.

TCS Employee Benefits

Summary:

Discretionary Annual Incentive.

Comprehensive Medical Coverage:
Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support:
Maternal & Parental Leaves.

Insurance Options:
Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth:
Commuter Benefits & Certification & Training Reimbursement.

Ti me Off:
Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance:
Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Salary Range: $100,000 - $115,000 a year