Agentic AI Developer
Job Location:
Job Location:
Richardson, TX - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
Yesterday
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Agentic AI Developer
Location: New York City NY NJ and Richardson TX (Onsite/Hybrid)
Hire Type: Contract
Location: New York City NY NJ and Richardson TX (Onsite/Hybrid)
Hire Type: Contract
Job Summary:
Infosys is seeking an experienced Agentic AI Developer to design develop and deploy autonomous AI agents capable of reasoning planning and executing complex tasks using LLM-based architectures. The ideal candidate will have strong expertise in Generative AI multi-agent systems orchestration frameworks and production-grade AI deployments.
Key Responsibilities:
Design and implement Agentic AI systems leveraging LLMs and tool-using autonomous agents.
Develop AI agents capable of multi-step reasoning planning memory management and task execution.
Build workflows using frameworks such as LangChain AutoGen CrewAI Semantic Kernel or similar.
Integrate LLMs (OpenAI Anthropic Azure OpenAI etc.) with enterprise data sources and APIs.
Develop RAG (Retrieval-Augmented Generation) pipelines with vector databases (Pinecone FAISS Weaviate etc.).
Implement multi-agent collaboration and orchestration strategies.
Optimize prompt engineering model performance latency and cost.
Deploy AI systems on cloud platforms (AWS/Azure/GCP) with MLOps best practices.
Ensure security governance and responsible AI compliance.
Collaborate with product architecture and data engineering teams for scalable AI solutions.
Required Qualifications:
5 years of software development experience (Python preferred).
2 years of hands-on experience with Generative AI / LLM-based application development.
Strong understanding of:
o Agentic workflows & autonomous agents
o Prompt engineering
o RAG architectures
o Vector databases
o API integrations
Experience with frameworks such as:
o LangChain
o AutoGen
o CrewAI
o Semantic Kernel
Experience deploying AI workloads on AWS/Azure.
Strong knowledge of REST APIs microservices Docker Kubernetes.
Familiarity with CI/CD and MLOps pipelines.
Preferred Qualifications:
Knowledge of reinforcement learning or planning algorithms.
Experience with multi-modal models (text image audio).
Exposure to compliance risk and AI governance frameworks.
Nice to Have:
Experience with Knowledge Graphs
Experience fine-tuning LLMs
Exposure to AI safety and guardrail frameworks
Infosys is seeking an experienced Agentic AI Developer to design develop and deploy autonomous AI agents capable of reasoning planning and executing complex tasks using LLM-based architectures. The ideal candidate will have strong expertise in Generative AI multi-agent systems orchestration frameworks and production-grade AI deployments.
Key Responsibilities:
Design and implement Agentic AI systems leveraging LLMs and tool-using autonomous agents.
Develop AI agents capable of multi-step reasoning planning memory management and task execution.
Build workflows using frameworks such as LangChain AutoGen CrewAI Semantic Kernel or similar.
Integrate LLMs (OpenAI Anthropic Azure OpenAI etc.) with enterprise data sources and APIs.
Develop RAG (Retrieval-Augmented Generation) pipelines with vector databases (Pinecone FAISS Weaviate etc.).
Implement multi-agent collaboration and orchestration strategies.
Optimize prompt engineering model performance latency and cost.
Deploy AI systems on cloud platforms (AWS/Azure/GCP) with MLOps best practices.
Ensure security governance and responsible AI compliance.
Collaborate with product architecture and data engineering teams for scalable AI solutions.
Required Qualifications:
5 years of software development experience (Python preferred).
2 years of hands-on experience with Generative AI / LLM-based application development.
Strong understanding of:
o Agentic workflows & autonomous agents
o Prompt engineering
o RAG architectures
o Vector databases
o API integrations
Experience with frameworks such as:
o LangChain
o AutoGen
o CrewAI
o Semantic Kernel
Experience deploying AI workloads on AWS/Azure.
Strong knowledge of REST APIs microservices Docker Kubernetes.
Familiarity with CI/CD and MLOps pipelines.
Preferred Qualifications:
Knowledge of reinforcement learning or planning algorithms.
Experience with multi-modal models (text image audio).
Exposure to compliance risk and AI governance frameworks.
Nice to Have:
Experience with Knowledge Graphs
Experience fine-tuning LLMs
Exposure to AI safety and guardrail frameworks
