Cognizant - Senior AI Engineer - Agentic Systems

Job Title: Senior AI Engineer Agentic Systems

Experience: 4 - 12 years

Role Overview:

We are seeking a highly skilled Senior AI Engineer with deep expertise in AI Agent development, multi-agent architectures, and the latest agentic frameworks. This role involves designing, building, and deploying production-grade AI agents that can autonomously reason, plan, and collaborate across complex workflows. You will work on state-of-the-art agentic technologies, integrating them with enterprise systems to deliver scalable, intelligent solutions.

Key Responsibilities:

- Design & Develop AI Agents: Build advanced AI agents capable of autonomous decision-making, reasoning, and multi-step task execution.

- Multi-Agent Systems: Architect and implement multi-agent ecosystems for collaborative problem-solving and distributed intelligence.

- Agentic Frameworks & Orchestration: Leverage latest frameworks (e.g., LangGraph, AutoGen, CrewAI, OpenAI Swarm) to create robust agent workflows.

- Pro-Code Development: Write clean, efficient, and scalable code in Python, TypeScript, or other relevant languages for agent orchestration and integration.

- Integration & Deployment: Connect agents with APIs, databases, enterprise systems, and LLM backends (OpenAI, Anthropic, Azure AI, Google AI, etc.).

- Optimization & Monitoring: Implement evaluation, observability, and performance tuning for agentic systems in production.

- Innovation & Research: Stay ahead of emerging trends in agentic AI, LLM orchestration, and autonomous systems; propose new solutions and patterns.

- Collaboration: Work closely with data scientists, architects, and product teams to deliver enterprise-grade AI solutions.

Required Skills & Qualifications:

- 8 - 10 years of experience in AI/ML engineering, with at least 3+ years in LLM-based solutions.

- Strong proficiency in Python and experience with pro-code agent development.

- Hands-on experience with multi-agent frameworks (e.g., LangGraph, AutoGen, CrewAI, Swarm).

- Deep understanding of LLM orchestration, prompt engineering, and tool integration.

- Familiarity with vector databases, retrieval-augmented generation (RAG), and knowledge graphs.

- Experience deploying AI solutions on cloud platforms with a focus on agent deployment and orchestration:

1. Azure Cloud Azure AI services, Kubernetes, and agent orchestration pipelines.

2. Google Cloud Platform (GCP) AI/ML services, Vertex AI, containerized agent deployment.

- Proficiency with Google AI Developer Kit (ADK) for building and integrating AI solutions.

- Knowledge of observability tools for AI agents and evaluation frameworks.

- Strong problem-solving skills and ability to work in fast-paced, innovative environments.

Preferred Qualifications:

- Experience with agentic planning, memory architectures, and autonomous workflows.

- Contributions to open-source agentic frameworks or AI research.

- Familiarity with enterprise integration patterns and secure AI deployments.