GenAI engineer (CE58SF RM 3567)

Position: GenAI engineer (CE58SF RM 3567)

Shift timing : IST (with MT overlap)
Education Required: Bachelor’s / Masters / PhD: Bachelor’s

Must have skills:
Generative AI & LLMs Python & ML Libraries RAG & Vector Databases Agentic AI Workflows Data Pipelines (Ingestion, Preprocessing, etc.) Model Evaluation & A/B Testing Red-teaming & Vulnerability Assessment Cloud Platforms (Azure, AWS, GCP) APIs, Microservices, & Containerization Data Governance & Security Orchestration Libraries (e.g., LangGraph, Crew AI)

Good to have skills:
Fine-tuning & Parameter-efficient Tuning Multimodal Models & Retrieval

Job description:

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/model red-teaming and vulnerability assessments of LLMs and chat systems using tools like Garak
(Generative AI Red-teaming & Assessment Kit).

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.

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