Senior Backend Engineer in Gen-AI

Roles & Responsibilities:

The Senior backend dev Engineer focuses on fine-tuning and optimizing large language models to meet the customer’s SDLC requirements, ensuring relevant outputs for tasks like code suggestions and documentation.

Optimize model performance for specific use cases and integrate LLMs into SDLC workflows.

The role involves managing vector and graph databases to support efficient data retrieval in the GenAI pipeline, designing and maintaining database structures, and optimizing query performance for the RAG pipeline.

Additionally, work closely with AI engineers to align data needs with model performance and implement strategies for scaling the database systems to support growth.

Qualifications, Education, Certifications and/or Other Professional Credentials

·       7 years in Python, Java or equivalent programming languages

·       4 years on cloud providers such as Azure/GCP/AWS

·       3 years of experience building GenAI services & platforms e.g. adapting models, build RAG pipelines

·       3 years of experience and familiarity with AI/ML Frameworks such as Pytorch/Tensor flow

·       At least 3 Realtime Gen AI project implementation in following areas

o  Dev Assistance [ Code generator, Test generator etc.]

o  RAG pipeline end to end understanding and implementation.

o  Graph or any retrieval method is added advantage.

o  At least 2 years of experience, where integrating with various LLM models has done successfully.

·       Build services using FASTAPI/Flask/Django

·       3 years’ experience working with a wide variety of backend data systems such as Big Q, snowflake having experience in data extraction experience in

o  streaming platform like kafka,

o  building data pipelines,

o  preparing data sets

·       3 Years of experience with DevSecOps flows leveraging technologies such as Git, Jenkins, Docker containers, Kubernetes, EKS and AKS, Datadogm Prometheus

·       7 years of experience in IT, preferably at least 2 years in cloud

·       Certifications by cloud providers- GCP is preferred. (certificate in BigQ, VertexAI is an added advantage)

·       Experience writing Libraries and Tools

Good to Have Tools:

• Testing Frameworks: pytest, JUnit (for testing integrations).
• Version Control: Git (to manage SDLC workflow integration).
• Collaboration Tools: Slack, Jira (for communication and project tracking).
• Multi-Agent Frameworks: Experience with frameworks that support multi-agent coordination and interactions.