AI Engineer

Unify Consulting is a leading AI management consulting firm that specializes in helping clients navigate challenges through innovative solutions. They are seeking an AI Engineer to design and build LLM-powered applications and agentic systems, focusing on production-ready solutions and quality user experiences.

Responsibilities

• Build GenAI / LLM applications
• Design and develop LLM-powered applications using enterprise AI platforms (e.g., AWS Bedrock, Azure OpenAI / Azure AI platforms, Google Vertex AI). Implement multi-step orchestration workflows that translate user intent into reliable actions and explainable outputs. Build robust RAG pipelines (vector databases, embeddings, chunking strategies) and validate grounding quality
• Engineer agentic solutions (Plan → Reason → Execute → Feedback)
• Design agent reasoning/control patterns (e.g., planning vs execution separation, tool calling, memory/context management).Integrate agents with tools/APIs and enterprise workflows with appropriate governance and guardrails
• Prompt engineering + evaluation
• Create reusable prompt templates/libraries; implement prompt testing frameworks; establish prompt versioning/governance.Evaluate solutions for quality/safety/latency/cost and iterate quickly
• Production readiness + operations
• Partner with platform/LLMOps teammates to deploy, monitor, and improve LLM systems in production.Build observability and reliability mechanisms for agent-based workflows
• Client-facing consulting
• Lead technical discovery, map workflows/pain points, and communicate solutions to technical and executive stakeholders

Skills

• 1–2+ years hands-on GenAI / Agentic AI experience building LLM apps on enterprise platforms (AWS Bedrock / Vertex AI / Azure AI platforms) in a professional setting
• Strong backend engineering experience (Python preferred) delivering production-grade systems
• Hands on professional experience with RAG patterns and implementation
• Ability to communicate clearly and contribute in fast-moving, cross-functional teams
• Computer Science / strong CS fundamentals
• Applied Scientist style skills: deep learning/NLP with PyTorch/TensorFlow + Hugging Face; ability to interpret research and implement emerging techniques
• Fine-tuning and optimization methods (LoRA/PEFT/QLoRA), distillation/quantization/pruning, GPU memory optimization
• Experience building secure tool integrations / agent middleware (tool schemas, SaaS integrations like Salesforce/SAP/ServiceNow, OAuth2, API security)
• Evaluation harnesses and regression testing for prompts/agents; RAG quality testing
• Cloud-native experience in large enterprise environments

Company Overview