Senior Applied AI Engineer

Role Overview

1. Applied LLM Engineering

• Design and implement RAG pipelines (chunking, embeddings, retrieval tuning)
• Optimize prompt structures for reliability and consistency
• Implement hallucination mitigation and output validation
• Design guardrails against prompt injection and misuse
• Manage context windows and token optimization strategies
• Build agent-based workflows when required

2. Enterprise Integration

• Integrate AI solutions with enterprise systems, including:
• Oracle
• Salesforce
• CRM / ERP platforms
• Work with structured enterprise datasets (leads, transactions, workflows)
• Design APIs and connectors to fetch and enrich enterprise data
• Handle authentication and secure integrations
• Ensure data governance and compliance standards
• *Experience with Oracle Cloud Infrastructure, Salesforce APIs, or similar enterprise platforms is a strong advantage.*

3. Backend & Architecture

• Develop scalable APIs using FastAPI or similar frameworks
• Integrate vector databases (FAISS, Qdrant, Milvus)
• Work with PostgreSQL, Redis, and other storage systems
• Design async workflows and background processing systems
• Ensure clean, modular, maintainable codebases

4. Production & Deployment

• Deploy AI services on AWS / Azure / OCI
• Containerization using Docker
• Monitor latency, token usage, and cost
• Implement logging and observability for AI outputs
• Optimize inference-heavy workloads

Required Skills

• 5+ years in software engineering or AI engineering
• Strong Python expertise
• Proven experience building LLM-based systems in production
• Strong understanding of RAG architectures, embeddings, and retrieval strategies
• Familiarity with token economics and latency trade-offs
• Knowledge of prompt injection risks and hallucination behavior
• Experience integrating APIs with enterprise systems
• Strong system design knowledge
• Hands-on experience with video generation models (like Veo, Seedance) and with running/integrating local LLMs and local LLM frameworks

Strong Advantage

• Experience working with Oracle ecosystem
• Experience working with Salesforce ecosystem
• Experience building AI-driven CRM enrichment pipelines
• Experience handling large-scale enterprise data flows
• Prior experience in high-ownership AI roles

Ideal Candidate Profile

• We are looking for someone who:
• Is among the top tier in applied AI system knowledge
• Understands real-world LLM nuances beyond surface-level prompting
• Has shipped AI systems into enterprise environments
• Can independently own architecture decisions
• Thinks in terms of reliability, scale, and governance