GEN AI Engineer

Job Role : GEN AI Engineer

Location: Hartford, Connecticut, United States

Job Description:

Responsibilities:

• Design and build fault-tolerant infrastructure to support the Generative AI Ref architecture (RAG, Summarization, Agent etc).

• Ensure code is delivered without vulnerabilities by enforcing engineering practices, code scanning, etc.

• Build and maintain IAC (terraform/Cloud Formation), CICD (Jenkins) scripts,CodePipeline, uDeploy, & GitHub Actions.

• Partner with our shared service teams like Architecture, Cloud, Security, etc to design and implement platform solutions.

• Collaborate with the DS team to develop a self-service internal developer Generative AI platform.

• Design and build the Data ingestion pipeline for Finetuning LLM Models.

• Create templates (Architecture As Code) implementing Ref architecture application’s topology.

• Build a feedback system using HITL for Supervised finetuning.

Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, or a technical field.

• 6 years of experience with AWS cloud.

• At least 8 years of experience designing and building data-intensive solutions using distributed computing.

• 12 years building and shipping software and/or platform infrastructure solutions for enterprises.

• Experience with CI/CD pipelines, Automated Testing, Automated Deployments, Agile methodologies, Unit Testing and Integration Testing tools.

• Experience with building scalable serverless application (real-time / batch) on AWS stack (Lambda step function)

• Knowledge of distributed NoSQL database systems.

• Experience with data engineering, ETL technology, and conversation UX is a plus.

• Experience with HPCs, vector embedding, and Hybrid/Semantic search technologies.

• Experience with AWS OpenSearch, Step/Lambda Functions, SageMaker, API Gateways, ECS/Docker is a plus.

• Proficiency in customization techniques across various stages of the RAG pipeline, including model fine-tuning, retrieval re-ranking, and hierarchical navigable small-world graph (HNSW) is a plus.

• Strong proficiency in embeddings, ANN/KNN, vector stores, database optimization, & performance tuning.

• Extensive programming experience with Python, Java.

• Experience with LLM orchestration frameworks like Langchain, LlamaIndex etc.

• Foundational understanding of Natural Language Processing, and Deep Learning.

• Experience with CI/CD pipelines, Automated Testing, Automated Deployments, Agile methodologies, Unit Testing, and Integration Testing tools.

• Excellent problem-solving skills and the ability to work in a collaborative team environment.

Excellent communication skills.""