Senior Gen AI Engineer

Space Inventive; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Space Inventive in India seeks a Senior AI/ML Engineer to design, develop, and deploy AI-driven GenAI solutions using AWS Bedrock and LLMs. You will collaborate with data scientists, product teams, and cloud engineers to build scalable AI apps and intelligent automation across business processes.

The ideal candidate has 4+ years in ML/AI projects, strong Python, and hands-on GenAI experience including RAG, embeddings and vector databases; cloud-native delivery and MLOps experience are expected.

Qualifications

• 4+ years of experience in ML/AI projects with hands-on GenAI delivery.
• Strong Python programming and cloud experience with AWS Bedrock.
• Experience with prompt engineering, RAG, embeddings, and vector stores.

Responsibilities

• Design, develop, and deploy AI/ML solutions using GenAI tech.
• Build GenAI apps with Bedrock, foundation models, and prompts.
• Develop RAG architectures for enterprise AI use cases.
• Fine-tune and optimize LLMs and evaluate model performance.
• Create scalable AI services and APIs using Python and cloud-native apps.
• Develop data pipelines for model training, inference, monitoring.
• Integrate vector databases for semantic search and retrieval.
• Collaborate with data scientists, product teams, and cloud engineers.
• Implement MLOps, model versioning, monitoring, and deployment automation.
• Ensure security, governance, and responsible AI in production.
• Stay updated on AI advancements, GenAI frameworks, and AWS services.

Skills

Python

GenAI & LLMs

AWS Bedrock

MLOps

Prompt Engineering

Vector databases

REST APIs

Tools

LangChain

LangGraph

LlamaIndex

Weaviate

OpenSearch

PyTorch

TensorFlow

Job description

Experience: 4+ Years

About the role :

We are seeking a highly skilled Senior AI/ML Engineer with hands-on experience in Generative AI, Large Language Models (LLMs), AWS Bedrock, and Machine Learning Engineering. The ideal candidate will be responsible for designing, developing, and deploying AI-driven solutions leveraging cutting-edge GenAI technologies and AWS cloud services. You will work closely with data scientists, product teams, and cloud engineers to build scalable AI applications and intelligent automation solutions.

Key Responsibilities :

• Design, develop, and deploy AI/ML solutions using modern machine learning and Generative AI technologies.
• Build and implement GenAI applications using Amazon Bedrock, foundation models (Claude, Llama, Titan, etc.), and prompt engineering techniques.
• Develop Retrieval-Augmented Generation (RAG) architectures for enterprise AI use cases.
• Fine-tune, evaluate, and optimize Large Language Models (LLMs).
• Create scalable AI services and APIs using Python and cloud-native architectures.
• Develop data pipelines for AI model training, inference, and monitoring.
• Integrate vector databases and embedding models for semantic search and knowledge retrieval.
• Collaborate with cross-functional teams to translate business requirements into AI solutions.
• Implement MLOps best practices, model versioning, monitoring, and deployment automation.
• Ensure security, governance, and responsible AI practices in production environments.
• Stay updated with advancements in AI, LLMs, GenAI frameworks, and AWS services.

Required Skills & Experience

• 4+ Years of experience in Machine Learning, Artificial Intelligence, or Data Science projects.
• Hands-on experience in Generative AI/LLM-based application development.
• Strong programming skills in Python.
• Hands-on experience with AWS Bedrock and AWS AI/ML services.
• Experience in Prompt Engineering, RAG, embeddings, and vector databases.
• Strong understanding of LLMs, Foundation Models, Transformers, and NLP concepts.
• Experience with LangChain, LangGraph, LlamaIndex, AWS Strands, or similar GenAI frameworks.
• Knowledge of PyTorch, TensorFlow, Scikit-learn.
• Experience with AWS Lambda, ECS/EKS, S3, API Gateway, SageMaker, CloudWatch.
• Familiarity with vector databases such as FAISS, ChromaDB, Weaviate, or OpenSearch.
• Experience building REST APIs using FastAPI or Flask.
• Strong understanding of model evaluation, performance optimization, and ML lifecycle management.