Agentic AI with Python

Vibehackers; Coimbatore District; On-site; INR 4,000,000 - 9,000,000; Full time

Job summary

Vibehackers in India is seeking a Senior Agentic AI Engineer to design, build, and deploy multi-agent, LLM-powered workflows and production-grade AI services using Python on AWS. You will architect agent orchestration, integrate agents with enterprise systems, and lead an offshore AI sub-team.

You will work on RAG pipelines, embeddings, semantic search, vector databases, and memory optimization while collaborating with product teams and data scientists to deliver scalable AI solutions.

Qualifications

• 8–12 years of software/AI engineering experience.
• Proven experience building agentic AI / multi-agent orchestration.
• Hands-on experience with LangChain and LangGraph.
• Strong understanding of LLMs, prompt engineering, tool calling/function calling, memory, and agent workflows.
• Hands-on experience with AWS Bedrock and/or AWS AgentCore.
• Knowledge of RAG, embeddings, semantic search, and vector databases.

Responsibilities

• Design and develop agentic AI workflows involving planning, reasoning, tool usage, memory, and orchestration.
• Build scalable LLM-powered applications using Python, LangChain, and LangGraph.
• Develop and integrate AI agents using AWS Bedrock and/or AWS AgentCore.
• Implement RAG pipelines, embeddings, semantic search, and vector database integrations.
• Integrate AI agents with enterprise APIs, databases, and other data sources.
• Design multi-agent architectures and orchestration patterns for complex business workflows.
• Optimize prompts, agent memory, orchestration, latency, and inference performance.
• Develop reusable frameworks, components, and engineering standards for agentic AI solutions.
• Deploy, monitor, troubleshoot, and harden AI services running on AWS, ensuring security, scalability, observability, and reliability.
• Collaborate with architects, product teams, data scientists, and software engineers; lead and mentor the offshore AI sub-team and conduct technical reviews.

Skills

Agent orchestration

Prompt engineering

LLM engineering

Python development

Memory management

API integration

CI/CD

Observability

Team leadership

Tools

LangChain

LangGraph

AWS Bedrock

AWS AgentCore

Lambda

ECS/EKS

S3

OpenSearch

DynamoDB

API Gateway

CloudWatch

Job description

Directly builds agentic LLM workflows with LangChain/LangGraph and AWS Bedrock — clearly aligned with vibe coding and rapid AI prototyping.

About the Role

Senior Agentic AI Engineer role to design, build, and deploy multi-agent, LLM-powered workflows and production-grade AI services using Python on AWS. The primary goal is to develop scalable agentic AI applications and frameworks (planning, memory, orchestration, RAG/vector search) and lead an offshore AI sub-team.

Role

Senior Agentic AI Engineer responsible for designing and implementing multi-agent, LLM-powered workflows and production-grade AI services using Python on AWS. The role includes architecting agent orchestration, integrating agents with enterprise systems, optimizing inference and memory, and leading an offshore AI sub-team.

Key Responsibilities

• Design and develop agentic AI workflows involving planning, reasoning, tool usage, memory, and orchestration.
• Build scalable LLM-powered applications using Python, LangChain, and LangGraph.
• Develop and integrate AI agents using AWS Bedrock and/or AWS AgentCore.
• Implement RAG pipelines, embeddings, semantic search, and vector database integrations.
• Integrate AI agents with enterprise APIs, applications, databases, and other data sources.
• Design multi-agent architectures and orchestration patterns for complex business workflows.
• Optimize prompts, agent memory, orchestration, latency, and inference performance.
• Develop reusable frameworks, components, and engineering standards for agentic AI solutions.
• Deploy, monitor, troubleshoot, and harden AI services running on AWS, ensuring security, scalability, observability, and reliability.
• Collaborate with architects, product teams, data scientists, and software engineers; lead and mentor the offshore AI sub-team and conduct technical reviews.

Requirements

• 8–12 years of experience in software engineering / AI engineering.
• Proven experience building agentic AI / generative AI applications and designing multi-agent orchestration.
• Hands‑on experience with LangChain and/or LangGraph.
• Strong understanding of LLMs, prompt engineering, tool calling/function calling, memory, and agent workflows.
• Hands‑on experience with AWS Bedrock and/or AWS AgentCore.
• Strong experience with RAG, embeddings, semantic search, and vector databases.
• Experience integrating AI agents with enterprise APIs, databases, and external tools.
• Experience deploying and operating production-grade AI services on AWS.
• Solid software engineering fundamentals: APIs, microservices, testing, and CI/CD.

Preferred / Nice-to-Have

• Experience in Insurance / Underwriting domain.
• AWS certification.
• Experience with MLOps / LLMOps and AI observability/evaluation.
• Exposure to AWS services such as Lambda, ECS/EKS, S3, OpenSearch, DynamoDB, API Gateway, CloudWatch.
• Experience leading or mentoring AI engineering teams.

Python AWS AWS Bedrock AWS AgentCore LangChain LangGraph RAG Embeddings Vector Databases Semantic Search Lambda ECS EKS S3 OpenSearch DynamoDB API Gateway CloudWatch CI/CD MLOps LLMOps

Skills

Software Engineering Python Development System Design Architecture Prompt Engineering Multi-agent Orchestration API Integration Microservices CI/CD Deployment and Operations Observability Performance Optimization Team Leadership Mentoring Collaboration