Job Title

Role OverviewWe are hiring a Senior Applied AI Engineer to design and deploy production-grade AI systems integrated with enterprise platforms such as Oracle, Salesforce, and other business ecosystems.This role requires deep understanding of modern LLM behavior, RAG architectures, system design, and backend engineering — along with the ability to integrate AI into structured enterprise data environments.This is a 6-Month Contract/Extendable.Key Responsibilities1. Applied LLM EngineeringDesign and implement RAG pipelines (chunking, embeddings, retrieval tuning)Optimize prompt structures for reliability and consistencyImplement hallucination mitigation and output validationDesign guardrails against prompt injection and misuseManage context windows and token optimization strategiesBuild agent-based workflows when required2. Enterprise IntegrationIntegrate AI solutions with enterprise systems, including:OracleSalesforceCRM / ERP platformsWork with structured enterprise datasets (leads, transactions, workflows)Design APIs and connectors to fetch and enrich enterprise dataHandle authentication and secure integrationsEnsure data governance and compliance standardsExperience with Oracle Cloud Infrastructure, Salesforce APIs, or similar enterprise platforms is a strong advantage.3. Backend & ArchitectureDevelop scalable APIs using FastAPI or similar frameworksIntegrate vector databases (FAISS, Qdrant, Milvus)Work with PostgreSQL, Redis, and other storage systemsDesign async workflows and background processing systemsEnsure clean, modular, maintainable codebases4. Production & DeploymentDeploy AI services on AWS / Azure / OCIContainerization using DockerMonitor latency, token usage, and costImplement logging and observability for AI outputsOptimize inference-heavy workloadsRequired Skills5+ years in software engineering or AI engineeringStrong Python expertiseProven experience building LLM-based systems in productionStrong understanding of RAG architectures, embeddings, and retrieval strategiesFamiliarity with token economics and latency trade-offsKnowledge of prompt injection risks and hallucination behaviorExperience integrating APIs with enterprise systemsStrong system design knowledgeHands-on experience with video generation models (like Veo, Seedance) and with running/integrating local LLMs and local LLM frameworksStrong AdvantageExperience working with Oracle ecosystemExperience working with Salesforce ecosystemExperience building AI-driven CRM enrichment pipelinesExperience handling large-scale enterprise data flowsPrior experience in high-ownership AI rolesIdeal Candidate ProfileWe are looking for someone who:Is among the top tier in applied AI system knowledgeUnderstands real-world LLM nuances beyond surface-level promptingHas shipped AI systems into enterprise environmentsCan independently own architecture decisionsThinks in terms of reliability, scale, and governance