GenAI Engineer | Hyderabad – Hybrid

About the Role:

We are seeking a skilled GenAI Engineer with approximately 3 years of experience to join our dynamic team. You will play a crucial role in developing and deploying cutting-edge AI-driven solutions, working directly with our AI/GenAI Architect to implement advanced multi-agent systems and conversational AI for enterprise applications. This is an opportunity to be at the forefront of AI innovation, building solutions that deliver real-world impact.

What You’ll Do

• Engineering & Implementation: Develop and deploy conversational agents, context-sensitive document handlers, and automated content workflows using Large Language Models (LLMs).
• Context Engineering: Design and implement strategies for managing and manipulating data context to improve model performance and relevance in our applications.
• Multi-Agent Systems Development: Implement and integrate components of multi-agent systems, focusing on effective agent orchestration, modular workflows, and seamless agent-to-agent interactions.
• System Integration & Pipelines: Build robust pipelines for knowledge retrieval (RAG), embedding services, and secure, scalable connectors to integrate with enterprise systems.
• Monitoring & Observability: Implement logging, tracing, and monitoring to ensure the reliability and optimal performance of our AI systems.

What We’re Looking For

• Bachelor’s degree in Computer Science, AI, Data Science, or a related field.
• Around 2 years of professional experience in AI/ML engineering, with a focus on Generative AI and LLM technologies.
• Strong problem-solving skills and an analytical mindset.
• Excellent communication skills and the ability to work collaboratively in an agile environment.
• A passion for staying updated on emerging AI/GenAI technologies and trends.

Required Technical Proficiencies

• Programming & Frameworks: Proficiency in Python and its core data science libraries.
• Generative AI & LLMs:
• Practical experience with prompt engineering and advanced fine-tuning techniques.
• Experience with context engineering to manage and enhance model context.
• Understanding of Retrieval-Augmented Generation (RAG) architectures and their implementation.
• Experience with multi-agent orchestration frameworks like LangGraph, Agno, AutoGen, or CrewAI.
• Familiarity with LLM application frameworks such as LangChain or LlamaIndex.

Databases & Storage:

• Experience with vector databases for RAG implementations (Pinecone, Milvus, ChromaDB, or others).
• Knowledge of traditional and non-traditional data storage solutions.
• Cloud & Deployment:
• Experience building and deploying GenAI agents using cloud-native tools on AWS (e.g., Amazon Bedrock Agents) or Azure (e.g., Azure AI Foundry Agent Service).

Good to Have

• Proficiency in containerization and orchestration tools like Docker and Kubernetes.
• Experience with Infrastructure-as-Code (IaC) using Terraform.
• Familiarity with foundational AI/ML frameworks like PyTorch or TensorFlow.

Education – BE/B.Tech/ME/M.Tech/MCA/MSc (Computers)

Interview rounds – 3 Technical rounds

Experience level: 2-5 Years

If you’re interested in this opportunity, we’d be happy to receive your updated CV. Simply click the email link below, or copy and paste the email address: careers@innominds.com or rvadde@innominds.com