Description : This requirement is for our MNC Aerospace domain client - WFO mode 5 days a week. Payroll company will be - Speed Engineering Solutions.

Key Responsibilities :

- Architect and build GenAI-powered applications using LLMs and advanced RAG pipelines for technical documentation, maintenance, and support workflows.

- Design and implement 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 innovative GenAI solutions.

- Stay current with GenAI trends, frameworks, and best practices to future-proof solutions for evolving enterprise needs.

Skill and Experience Required :

Experience Range : 4-8 Years

Qualification : Bachelors or Masters Degree in Computer Science or any other B.E. / B.Tech.

- 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.

- Experience in Graph Database like Neo04/ Amazon Neptune is a must.

- 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.

- 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.

Location : Bangalore, Karnataka

Looking only Immediate Joiners, others please don't apply.