Principal Agentic AI Engineer

Job Summary

We are seeking an experienced Agentic AI Technical Lead to lead a high-impact Agentic AI SWAT Pod responsible for delivering next-generation AI solutions across strategic business use cases.

This is a hands-on technical leadership role where you will architect, build, review, troubleshoot, and deploy production-grade AI applications while mentoring a compact engineering team. You will drive the adoption of modern Agentic AI architectures, intelligent workflows, Retrieval-Augmented Generation (RAG), and orchestration frameworks to deliver scalable enterprise AI solutions.

The ideal candidate should possess a strong software engineering background with recent hands-on coding experience in AI applications and have successfully delivered production-grade LLM, RAG, or Agentic AI solutions.

Key Responsibilities

Technical Leadership

• Lead a compact Agentic AI SWAT Pod across multiple AI use-case tracks.
• Drive technical architecture and implementation for enterprise Agentic AI solutions.
• Select the most appropriate solution architecture using:
  • Agentic AI
  • Workflow Automation
  • Retrieval-Augmented Generation (RAG)
  • Application Logic
  • Hybrid AI Patterns
• Mentor engineers, conduct code reviews, and establish engineering best practices.
• Parallelize delivery across multiple workstreams while ensuring technical consistency.

AI Solution Development

• Design and develop production-ready AI agents and autonomous workflows.
• Build intelligent AI systems using:
  • Large Language Models (LLMs)
  • RAG architectures
  • Multi-agent orchestration
• Develop reusable AI components and reference implementations.
• Own critical code paths and contribute to hands-on software development.

Agent Orchestration Integration

• Take ownership of:
  • Agent orchestration
  • MCP (Model Context Protocol) tools
  • Context management
  • Prompt orchestration
  • Retrieval pipelines
  • AI workflow readiness
  • AI service integrations

Engineering Excellence

• Design scalable, secure, and maintainable AI platforms.
• Troubleshoot production issues and optimize AI workloads.
• Implement CI/CD best practices for AI applications.
• Build observability into AI systems using modern monitoring frameworks.
• Ensure engineering quality through testing, code reviews, and deployment automation.

Required Skills Experience

• 10+ years of software engineering, platform engineering, or AI development experience.
• Recent hands-on coding experience in production environments.
• Proven experience delivering:
  • Large Language Model (LLM) applications
  • Agentic AI solutions
  • AI Assistants / Intelligent Agents
• Strong software engineering fundamentals.
• Experience building scalable enterprise AI applications.
• Strong understanding of API development, cloud-native architecture, and distributed systems.
• Experience implementing CI/CD pipelines and production monitoring.

Primary Skills

Programming Languages

• Python
• Java
• TypeScript

AI Machine Learning

• AI Assistants
• AI Orchestration
• Prompt Engineering

Frameworks Technologies

• LangGraph
• MCP (Model Context Protocol)
• AI Workflow Orchestration

Cloud Platform

• Kubernetes
• REST APIs
• Cloud Platforms (Azure / AWS / GCP)

DevOps

• CI/CD Pipelines
• Git
• Deployment Automation

Observability

• OpenTelemetry
• Monitoring Logging
• Performance Optimization

Secondary Skills (Good to Have)

• LangChain
• CrewAI
• AutoGen
• Semantic Kernel
• Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate)
• Knowledge Graphs
• Prompt Optimization
• Multi-Agent Systems
• Docker
• Microservices Architecture
• Distributed Systems
• Event-Driven Architecture
• Cloud Security
• MLOps
• AI Governance
• Enterprise Architecture

Disclaimer: This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.