Senior AI Engineer – GenAI & Data Platform (AWS)

We are seeking a highly skilled Senior AI Engineer to design, build, and scale enterprise-grade Generative AI and Data Platforms on AWS. This role will be responsible for delivering production-ready AI solutions leveraging LLMs, vector search, graph databases, and governed data pipelines. The ideal candidate will drive end-to-end AI lifecycle implementation, from data ingestion and knowledge engineering to API development, deployment, and operational excellence. Key Responsibilities Generative AI & LLM Engineering • Design and implement LLM-powered applications using RAG architectures, embeddings, and prompt engineering techniques. • Build vector search and retrieval systems using Amazon OpenSearch and vector databases. • Develop graph-based knowledge systems using Amazon Neptune for relationship mapping, explainability, and lineage tracking. • Implement agentic AI workflows using frameworks such as LangGraph, AutoGen, and CrewAI. • Integrate and orchestrate LLM frameworks including LangChain and LlamaIndex. • Evaluate LLM models and retrieval strategies based on accuracy, latency, cost, and contextual effectiveness. Data Platform & Knowledge Engineering • Design and develop scalable data pipelines using Databricks and Apache Spark. • Build ingestion, transformation, document processing, chunking, metadata tagging, embedding generation, and indexing pipelines. • Establish data quality, governance, monitoring, lineage tracking, and access control frameworks. Backend & API Development • Develop secure, scalable backend services and APIs exposing AI capabilities. • Implement API versioning, reliability patterns, retry mechanisms, circuit breakers, and reusable platform services. Deployment & MLOps • Build and manage CI/CD pipelines for AI and data workloads. • Deploy and manage containerized applications using Docker and Kubernetes. • Implement blue-green deployments, canary releases, rollback strategies, feature flags, and observability solutions. • Monitor system health, latency, failures, cost, and data freshness while ensuring security and least-privilege access. LLM Observability & Governance • Define and track GenAI quality metrics including grounding, retrieval relevance, response consistency, latency, and cost. • Implement prompt management, version tracking, evaluation pipelines, and continuous improvement frameworks. • Ensure AI safety, responsible AI practices, data privacy, compliance, and auditability standards. Required Skills • Strong experience with Generative AI and Large Language Models (RAG, embeddings, prompt engineering). • Hands-on experience with AWS services including OpenSearch, Neptune, DynamoDB, and ElastiCache (Redis). • Expertise in vector search and retrieval systems. • Experience with graph databases and knowledge graph implementations. • Strong proficiency in LangChain, LlamaIndex, LangGraph, AutoGen, and CrewAI. • Excellent programming skills in Python and backend microservices development. • Experience with Databricks, Apache Spark, distributed systems, and API design. ABOUT BRICKRED SYSTEMS BrickRed Systems is a global leader in next-generation technology consulting and workforce solutions, specializing in delivering high-quality talent across digital, engineering, and business operations domains.With a strong emphasis on innovation, scalability, and client success, BrickRed Systems enables organizations to solve complex business challenges by providing skilled professionals in areas such as procurement, finance operations, data analytics, and technology.BrickRed fosters a culture of continuous learning, collaboration, and excellence, helping professionals work on high-impact global projects.