Paul's Techno Crafts - Senior Generative AI Engineer

Role Synopsis :

As a Senior GenAI Engineer, you will build and scale production-grade GenAI applications, including RAG chatbots, agentic workflows, and AI-powered enterprise tools on AWS.

Key Responsibilities :

Development (Core Focus) :

- Build :

i. RAG-based chatbots (Agentic & standard)

ii. Multi-agent workflows (LangGraph / LangChain)

iii. AI-powered search and recommendation systems

iv. Text-to-code and AI-over-data solutions

AI Engineering :

- Implement :

i. Document ingestion pipelines

ii. Embeddings and vector DB integrations

iii. Prompt engineering and optimization

- Develop Graph RAG pipelines using knowledge graphs

Evaluation & Guardrails :

- Implement :

i. Evaluation frameworks (RAGAS, DeepEval)

ii. Response validation and scoring pipelines

- Apply guardrails :

i. Hallucination reduction

ii. Safety filters

Platform & Integration :

- Work with AWS :

i. Bedrock, Lambda, API Gateway, S3

- Build :

i. Multi-modal AI pipelines (text + image + IoT data)

ii. Streaming/real-time inference pipelines

LLMOps & Deployment :

- CI/CD using Azure DevOps

- Logging, monitoring, and performance tuning

- Implement cost tracking and optimization (FinOps basics)

Collaboration :

- Work with architects and product teams

- Support deployments and production issues

Required Skills & Experience :

Core Technical :

- Strong in :

i. Python

ii. LangChain, LangGraph

iii. RAG pipelines and vector databases

- Hands-on experience with :

i. Evaluation frameworks (RAGAS, DeepEval)

ii. Basic Knowledge Graph / Graph RAG concepts

Cloud & DevOps :

- AWS (Bedrock preferred)

- CI/CD (Azure DevOps)

- API development

Advanced Capabilities :

- Exposure to :

i. Multi-modal AI

ii. Streaming / real-time systems

iii. AI cost optimization (FinOps basics)

Domain :

- IoT / Industrial domain (good to have)