Cummins
Artificial Intelligence Engineer
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Pune, Maharashtra, India
Work mode:
Onsite
Published on:
7 August 2026
What they need
Key Responsibilities
Agentic Solution Development
- Design and implement enterprise AI solutions using agentic workflows and orchestration frameworks
- Build multi-agent systems leveraging memory, planning, tool use, and MCP-style interactions
- Develop production-ready AI workflows integrating enterprise systems, APIs, and business tools
- Create reusable prompts, tools, agents, and orchestration pipelines
Enterprise Integration & Automation
- Integrate AI agents with enterprise applications, APIs, databases, SharePoint, SAP, ServiceNow, Jira, etc.
- Build secure tool-calling and data-access mechanisms for agent workflows
- Implement AI-assisted automation use cases across engineering, operations, safety, and business domains
Solution Architecture & Engineering
- Collaborate on architecture design for scalable AI systems
- Develop backend services, APIs, orchestration layers, and deployment pipelines
- Optimize AI workflows for latency, reliability, scalability, and observability
- Support cloud-native deployments on Azure/AWS
Value Realization
- Work closely with business stakeholders to identify impactful use cases
- Quantify business impact including productivity, cost savings, quality improvements, and automation efficiency
- Support pilot rollouts and transition of PoCs into production
Collaboration & Innovation
- Contribute reusable frameworks, templates, and accelerators
- Stay updated with evolving AI ecosystems including OpenAI, LangChain, AutoGen, CrewAI, MCP, and orchestration frameworks
- Mentor junior developers and contribute to AI engineering best practices
Required Skills
Technical Skills
Strong programming experience in Python and/or Node.js
Hands-on experience with:
LangChain
LangGraph
CrewAI / AutoGen / Semantic Kernel
OpenAI APIs / Azure OpenAI
MCP concepts and integrations
Experience building REST APIs and enterprise integrations
Strong understanding of:
Agent orchestration
Tool calling
RAG architectures
Vector databases
Memory systems
Prompt engineering
Experience with cloud platforms (AWS preferred)
Familiarity with Docker, CI/CD, GitHub, and DevOps practices
Good to have Skills
- Experience with enterprise AI governance and security
- Knowledge of observability frameworks and evaluation methods
- Experience deploying AI systems in enterprise environments
- Exposure to frontend frameworks (React/Next.js) is a plus
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