Role: Sr. GenAI Engineer

Location: Bangalore

Experience: 7 to 12 Years

Key Responsibilities

We are seeking a experienced Generative AI developer to lead the design and development of an AI platform that leverages Large Language Models (LLMs) and other cutting-edge AI technologies.

In this role, your core responsibilities are

- Architect and build GenAI-powered applications using LLMs and advanced RAG pipelines for technical documentation, maintenance, and support workflows.
- Prompt Engineering and design of retrieval-augmented generation (RAG) systems leveraging vector databases and semantic search for contextual information retrieval.
- Integrate and fine-tune LLMs (OpenAI, Anthropic, Amazon Bedrock, HuggingFace, etc.) for domain-specific tasks and continuous improvement.
- Develop robust evaluation frameworks for LLM output (relevancy, faithfulness, summarization, contextual accuracy).
- Build and deploy microservices and APIs for GenAI solutions, ensuring high availability, scalability, and secure access.
- Collaborate with product, domain, and platform teams to refine requirements and deliver creative GenAI solutions.
- Stay current with GenAI trends, frameworks, and best practices to future-proof solutions for evolving enterprise needs

Candidate Skills & Requirements

- GenAI & LLMs: OpenAI, Anthropic, Amazon Bedrock, HuggingFace Transformers, LangChain, RAG architectures, prompt engineering, fine-tuning.
- Vector Databases & Semantic Search: Pinecone, FAISS, Milvus, Weaviate, Elasticsearch/OpenSearch with vector support.
- GenAI Evaluation & Monitoring: G-Eval, Prometheus, QAG scorer, MLflow, DataDog, CloudWatch, custom LLM-as-a-judge frameworks.
- API & Microservices: RESTful API design, GraphQL, FastAPI, Flask, OAuth2/JWT,



containerization (Docker, Kubernetes).
- Security & Compliance: IAM, KMS, VPC endpoints, S3 Object Lock, CloudTrail, encryption policies, GDPR/industry compliance.
- DevOps for GenAI: CI/CD pipelines (GitHub Actions, CodePipeline), Terraform, AWS CDK, CloudFormation for automated deployment and scaling of GenAI services.
- Data Modeling for GenAI: Metadata tagging, schema design, data quality management for LLM training and inference.
- Multi-modal Retrieval: Experience with text, images, video, telemetry for comprehensive GenAI solutions. Preferred Experience
- Building enterprise-grade RAG systems for technical documentation, support, or maintenance workflows.
- Implementing multi-modal retrieval in large-scale environments.
- Familiarity with continuous evaluation and improvement of LLMs in production (A/B testing, feedback loops).
- Exposure to regulated industries (aviation, manufacturing, healthcare) with strict compliance and audit requirements.
- Working with multi-cloud architectures (AWS/Azure/GCP) and hybrid deployments.
- Advanced knowledge of MLOps: model deployment, monitoring, rollback, and lifecycle management

Role: Aviation & Aerospace - Other, Industry Type: Aviation, Department: Aviation & Aerospace, Employment Type: Full Time, Permanent Role Category: Aviation & Aerospace - Other Education UG: B.Tech / B.E. in Computer Science and Engineering (CSE), Artificial Intelligence And Data Science, Artificial Intelligence And Machine Learning PG: M.Tech in Artificial Intelligence and Machine Learning Key Skills Skills highlighted with ‘‘ are preferred keyskills generative aiLLMRetrieval Augmented GenerationPredictive MaintenanceAWS Artificial IntelligenceMachine LearningData SciencePredictive Modeling

📌 Sr Gen AI Engineer (Bengaluru)
🏢 Safran Engineering Services
📍 Bengaluru