Senior Software Engineer-AI

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