Sr. AI Automation Engineer

Key Skills

• Agentic AI Workflows
• AI Orchestration
• APIs & MCP Integration

Job Summary

Key Responsibilities

• Design and implement AI-driven automation solutions to improve engineering and operational processes.
• Develop AI workflows, agent orchestration frameworks, and automation pipelines using modern AI platforms.
• Integrate LLMs, enterprise tools, and applications through APIs and workflow orchestration platforms.
• Build POCs, pilots, and reusable AI accelerators for enterprise adoption.
• Create intelligent remediation and automation solutions to reduce manual effort across development and infrastructure teams.
• Develop AI agents capable of performing multi-step tasks, decision-making, and workflow execution.
• Collaborate with product, engineering, infrastructure, security, and operations teams to identify automation opportunities.
• Establish best practices, governance, and reusable patterns for AI implementation.
• Support enterprise modernization initiatives through AI-enabled process transformation.
• Measure and report productivity gains, efficiency improvements, and business outcomes.

Mandatory Required Skills

• 8+ years of software engineering experience.
• 3+ years of hands-on experience in AI/ML, Generative AI, or intelligent automation initiatives.
• Strong experience with Python development.
• Hands-on experience with Generative AI, LLMs, and AI Agent frameworks.
• Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar AI agent frameworks.
• Strong understanding of prompt engineering, RAG, vector databases, and AI workflow design.
• Hands-on experience integrating enterprise applications using REST APIs and SDKs.
• Strong knowledge of API integration, authentication, token management, and workflow orchestration.
• Experience with automation platforms such as Power Automate, Zapier, n8n, or similar.
• Experience with AI orchestration and agentic AI workflows.
• Experience with API and MCP integration.
• Familiarity with Azure, AWS, or Google Cloud Platform cloud platforms.
• Experience with Git, CI/CD pipelines, and software development best practices.
• Strong problem-solving and stakeholder communication skills.
• Ability to work onsite from Day 1 in a hybrid environment, 3 days per week.

Preferred Qualifications

• Experience building enterprise AI agents and copilots.
• Knowledge of development, infrastructure, security, or vulnerability remediation processes.
• Experience implementing AI solutions for productivity improvement and process automation.
• Understanding of enterprise architecture and system integration patterns.
• Exposure to MLOps, observability, and AI governance frameworks.
• Prior experience leading enterprise automation or AI transformation initiatives.

Expected Outcomes

• Accelerate AI adoption across multiple technology organizations.
• Deliver reusable AI frameworks and automation accelerators.
• Reduce manual engineering effort through intelligent automation.
• Enable faster experimentation, innovation, and enterprise transformation.
• Drive measurable productivity and efficiency gains across teams.