USA_Developer

Pay rate range : $44.24-49.24 / hr.

GBaMS ReqID : 10383403

ROLE : Agentic AI Developer

Job Description :

Agentic AI systems preferably AWS Bedrock LLM, Python, AI agent frameworks such as LangGraph, LlamaIndex, LangChain, or AutoGen

Design, develop, and deploy agentic AI systems preferably AWS Bedrock LLM that enhance decision-making and automate workflows across various applications. Work at the intersection of backend engineering, applied machine learning, and agent orchestration, collaborating with cross-functional teams to translate business needs into robust, scalable, and ethical AI solutions.

Key Responsibilities :

• Agent Development : Design and implement intelligent agents capable of autonomous decision-making, task orchestration, and interaction with external APIs, tools, and databases.
• System Architecture : Architect and scale backend services, APIs, and microservices that support ML-driven and agentic AI applications. This includes designing infrastructure for agent tool use, memory, and planning.
• LLM Integration : Integrate large language models into complex enterprise workflows, CI / CD pipelines, and other business processes.
• Agent Orchestration : Build and prototype agentic workflows using advanced orchestration techniques and frameworks (e.g., LangGraph, CrewAI, AutoGen).
• Evaluation and Optimization : Build robust evaluation frameworks to measure agent performance, accuracy, and reliability, and continuously improve agent logic through prompt engineering and other optimization techniques.
• Collaboration : Partner with product managers, data scientists, DevOps engineers, and business stakeholders to gather requirements and drive the adoption of agentic AI solutions.
• AI Governance and Ethics : Ensure all solutions are aligned with enterprise security protocols, data governance policies, and ethical AI principles.
• Research and Innovation : Stay current with emerging trends and research in agentic AI and related technologies to inform strategic technical decisions.

Required Skills and Qualifications.

o7+ years of experience in AI / ML development, with a specific focus on agentic systems, autonomous workflows, or LLM-based applications.

oProven experience building production-level AI or ML systems.

oProgramming : Strong proficiency in Python is essential, with experience in backend frameworks like FastAPI or Flask.

oAI Frameworks : Hands-on experience with AI agent frameworks such as LangGraph, LlamaIndex, LangChain, or AutoGen.

oData and Storage : Expertise with vector databases (e.g., Pinecone, Weaviate, PGVector) and general databases (SQL and NoSQL).

oCloud Platforms : Experience with cloud environments (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).

oMLOps : Familiarity with MLOps principles and tools for deploying, monitoring, and managing AI agents in production.

oDeep understanding of LLMs and agentic AI concepts, including autonomous planning, reasoning chains, memory management, and tool use.

oExperience with advanced prompt engineering and orchestration logic. "

oProgramming : Strong proficiency in Python is essential, with experience in backend frameworks like FastAPI or Flask.

oAI Frameworks : Hands-on experience with AI agent frameworks such as LangGraph, LlamaIndex, LangChain, or AutoGen.

oData and Storage : Expertise with vector databases (e.g., Pinecone, Weaviate, PGVector) and general databases (SQL and NoSQL).

oCloud Platforms : Experience with cloud environments (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).

oMLOps : Familiarity with MLOps principles and tools for deploying, monitoring, and managing AI agents in production.

Experience requested : 7+ yrs

Skills : Category Name Required Importance Experience SkillCategoryTest1_MN Digital : Python Yes 1 7+ years