Gen AI Developer (Contract)

Saaki Argus & Averil Consulting; Chennai; In loco; INR 1.200.000 - 2.400.000; Tempo pieno

Descrizione del lavoro

Saaki Argus & Averil Consulting seeks an AI Software Engineer to design and maintain scalable Gen AI solutions. You will build LLM-powered apps, RAG pipelines, and agent-based architectures, leveraging Python, LangChain, and Bedrock to deliver enterprise-grade capabilities.

You will implement authentication, observability, and scalable containerized deployments with Docker, ensure security and data privacy, and collaborate with architects and product teams to translate requirements into

Competenze

• Proficiency in Python and building backend APIs
• Experience with Gen AI and LLM tooling
• Familiarity with RAG pipelines and vector databases

Mansioni

• Design, develop, and maintain scalable Gen AI applications using LLMs, RAG, and agent-based architectures.
• Develop and optimize backend APIs and microservices using Python and relevant frameworks.
• Build end-to-end RAG pipelines including ingestion, preprocessing, chunking, embeddings, retrieval, indexing.
• Work with vector databases for semantic search and context retrieval.
• Develop LLM applications using LangChain, LangGraph, and LangFuse.
• Implement and deploy LLM solutions using Amazon Bedrock and integrate foundation models into enterprise apps.
• Design intelligent AI agents including tool calling, orchestration, memory, and reasoning patterns.
• Develop system prompts and context-engineering strategies to improve accuracy and reliability.
• Implement SSO-based authentication and authorization for enterprise Gen AI apps.
• Containerize apps and services using Docker for scalable deployment.
• Implement observability and monitoring for APIs, LLM apps, model performance, latency, failures, and usage.
• Optimize for performance, scalability, reliability, security, and cost efficiency.
• Collaborate with architects, data engineers, product teams, and stakeholders to translate requirements into production-ready AI solutions.
• Follow best practices for Gen AI security, data privacy, prompt management, evaluation, and responsible AI.
• Troubleshoot production issues and enhance quality and performance of deployed Gen AI apps.

Conoscenze

Python

LLMs

RAG

LangChain

LangGraph

LangFuse

Amazon Bedrock

Vector databases

Docker

Observability

Security

Strumenti

Docker

LangChain

LangGraph

LangFuse

Amazon Bedrock

Vector databases

Descrizione del lavoro

• Design, develop, and maintain scalable Gen AI applications using LLMs, RAG, and agent-based architectures.
• Develop and optimize backend APIs and microservices using Python and relevant frameworks.
• Build end-to-end RAG pipelines, including document ingestion, preprocessing, chunking, embeddings, retrieval, and indexing.
• Work with vector databases for efficient semantic search and context retrieval.
• Develop LLM applications using LangChain, LangGraph, and LangFuse.
• Implement and deploy LLM solutions using Amazon Bedrock and integrate foundation models into enterprise applications.
• Design intelligent AI agents, including tool calling, workflow orchestration, memory, and multi-step reasoning patterns.
• Develop effective system prompts and context-engineering strategies to improve accuracy, relevance, and reliability of Gen AI applications.
• Implement SSO-based authentication and authorization for enterprise Gen AI applications.
• Containerize applications and services using Docker and support scalable deployment across enterprise environments.
• Implement observability and monitoring for APIs, LLM applications, model performance, latency, failures, and usage.
• Optimize applications for performance, scalability, reliability, security, and cost efficiency.
• Collaborate with architects, data engineers, product teams, and business stakeholders to translate requirements into production-ready AI solutions.
• Follow best practices for Gen AI security, data privacy, prompt management, evaluation, and responsible AI.
• Troubleshoot production issues and continuously enhance the quality and performance of deployed Gen AI applications.