Gen AI Engineer

Overview

Design, build and deploy production-grade generative AI and agentic AI solutions that operate on structured and unstructured data and enable AI-driven decision-making.

What you'll do

• Architect, develop, test and deploy generative AI solutions (online/offline LLMs, SLMs, TLMs) for domain-specific use cases.
• Design and implement agentic AI workflows and orchestration using frameworks such as LangGraph, Crew AI, or equivalent.
• Integrate enterprise knowledge bases and external data sources via vector databases and Retrieval-Augmented Generation (RAG).
• Build and productionize ingestion, preprocessing, indexing and retrieval pipelines for structured and unstructured data (text, tables, documents, images).
• Implement fine-tuning, prompt engineering, evaluation metrics, A/B testing and iterative model improvement cycles.
• Conduct red-teaming and vulnerability assessments of LLMs and chat systems using tools such as Garak.
• Collaborate with MLOps/platform teams to containerize, monitor, version and scale models (CI/CD, model registry, observability).
• Ensure model safety, bias mitigation, access controls and data privacy compliance in deployed solutions.
• Translate business requirements into technical designs with clear performance, cost and safety constraints.

What you'll need

• Experience in software engineering and AI-related roles.
• Minimum 2-3 years of direct experience with Generative AI and Large Language Models (LLMs).
• Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem).
• Hands-on experience with LLMs, RAG, vector databases and retrieval pipelines.
• Practical experience deploying agentic workflows and building multi-step, tool-enabled agents.
• Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments.
• Demonstrated experience implementing content filtering / moderation systems.
• Solid skills working with structured and unstructured data and advanced feature engineering.
• Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable).
• Experience building APIs/microservices, containerization (Docker) and orchestration (Kubernetes).
• Strong understanding of model evaluation, performance profiling, inference cost optimization and observability.
• Good knowledge of security, data governance and privacy best practices for AI systems.

Nice to have

• Hands-on fine-tuning experience and parameter-efficient tuning methods.
• Experience with multimodal models and retrieval-augmented multimodal pipelines.
• Prior work on agentic safety, tool-use constraints, LLM application firewalls or human-in-the-loop systems.
• Familiarity with LangChain, LangGraph, Crew AI or similar orchestration libraries.

Details

• Location: Indore, Madhya Pradesh, India (Vijaynagar, eInfochips).
• Employment type: Full time.