Agentic AI / Python Engineer
Remote · United States
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Estimated pay
Estimate$211K–$246K/yr
Estimate — the employer hasn't published pay.
Based on 8 similar mid-level Agentic AI jobs in United States that show pay. The range is the middle half of their posted pay (25th to 75th percentile), not an offer — ask the employer for the real range.
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Skills mentioned
About the role
This is a remote position.
Job Overview
We are seeking an experienced Agentic AI / Python Engineer for an opportunity with Cognizant. The role focuses on developing Python-based applications and intelligent AI solutions, with particular emphasis on Agentic AI, autonomous agents, and Large Language Model (LLM) integration.
The ideal candidate will have strong hands-on Python development experience and practical exposure to designing, implementing, and integrating AI-powered workflows and applications.
Key Responsibilities
Design, develop, and maintain scalable Python applications and backend services.
Develop Agentic AI solutions involving autonomous agents, intelligent workflows, and multi-agent systems.
Integrate Large Language Models (LLMs) into applications and business processes.
Build AI agent workflows involving tool calling, function calling, and external API integrations.
Design and implement RESTful APIs and backend services using Python.
Explore and implement Retrieval-Augmented Generation (RAG) solutions where applicable.
Collaborate with engineering teams to develop and improve AI-driven applications.
Support the integration, testing, deployment, and optimization of AI applications.
Contribute to the development of reliable, maintainable, and production-ready AI solutions.
Design, develop, and maintain scalable Python applications and backend services.
Develop Agentic AI solutions involving autonomous agents, intelligent workflows, and multi-agent systems.
Integrate Large Language Models (LLMs) into applications and business processes.
Build AI agent workflows involving tool calling, function calling, and external API integrations.
Design and implement RESTful APIs and backend services using Python.
Explore and implement Retrieval-Augmented Generation (RAG) solutions where applicable.
Collaborate with engineering teams to develop and improve AI-driven applications.
Support the integration, testing, deployment, and optimization of AI applications.
Contribute to the development of reliable, maintainable, and production-ready AI solutions.
Note:This is a preliminary job description prepared for recruitment purposes. Final responsibilities and engagement details are subject to client confirmation.
Requirements
Core Requirements
Strong hands-on experience in Python programming and software development.
Practical experience developing Agentic AI applications, AI agents, or autonomous AI workflows.
Experience integrating Large Language Models (LLMs) and Generative AI capabilities into applications.
Understanding of AI agent orchestration, multi-agent systems, and tool/function calling.
Experience designing and integrating APIs and Python-based backend services.
Ability to develop maintainable, scalable, and reliable software solutions.
Strong problem-solving skills and the ability to collaborate with technical teams.
Strong hands-on experience in Python programming and software development.
Practical experience developing Agentic AI applications, AI agents, or autonomous AI workflows.
Experience integrating Large Language Models (LLMs) and Generative AI capabilities into applications.
Understanding of AI agent orchestration, multi-agent systems, and tool/function calling.
Experience designing and integrating APIs and Python-based backend services.
Ability to develop maintainable, scalable, and reliable software solutions.
Strong problem-solving skills and the ability to collaborate with technical teams.
Preferred Technical Skills
Experience with Agentic AI frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
Familiarity with FastAPI, Flask, and REST APIs.
Knowledge of Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.
Experience with OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock, or Google Vertex AI.
Familiarity with Docker, Kubernetes, and cloud deployment environments.
Experience building, deploying, or maintaining AI applications in production.
Understanding of LLM evaluation, prompt engineering, and AI application testing.
Experience with Agentic AI frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
Familiarity with FastAPI, Flask, and REST APIs.
Knowledge of Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.
Experience with OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock, or Google Vertex AI.
Familiarity with Docker, Kubernetes, and cloud deployment environments.
Experience building, deploying, or maintaining AI applications in production.
Understanding of LLM evaluation, prompt engineering, and AI application testing.
Originally posted on Himalayas