AI Engineer (Contract): Production Agentic AI, RAG & LLM Systems on AWS Bedrock / Vertex AI

WHO WE ARE devx labs is an AI-native consulting company that fundamentally reimagines business operations around AI capabilities. We don't just implement AI tools, we transform how enterprises operate through first-principles thinking and outcome-driven execution. ABOUT THE ROLE As an AI Engineer, you'll build AI-native solutions that power transformative outcomes across Customer Interactions, AI-Led Business Operations and Enterprise Architecture. Every system you build, every agent you architect, every integration you design directly translates into measurable client value. This is not a "make the demo work" role. You're the builder who turns AI potential into production reality. RESPONSIBILITIES Build AI-Native Solutions (65%) - Design, build and deploy production-grade agentic AI systems: multi-agent workflows, RAG architectures, LLM-powered automation and intelligent data pipelines on AWS and Gemini Enterprise / Google Cloud - Architect for enterprise scale: thousands of users, millions of transactions - Use AI-assisted development to ship 2-3x faster while maintaining quality and reliability - Own technical decisions: AI stack, model, framework and architecture, balancing performance, cost and maintainability - Build across practices: customer service agents, inventory intelligence, enterprise integration platforms Drive Client Success (25%) - Join discovery workshops, understand client pain points and architect solutions with measurable outcomes - Present solutions to client stakeholders and explain architectural decisions with confidence - Work embedded with client teams, gather usage insights and optimise for adoption and impact - Work with Solutions Consultants and Practice Leaders to turn strategy into technical roadmaps Mentor & Multiply (10%) - Guide junior engineers through code reviews and architectural thinking - Document patterns, build reusable accelerators and technical playbooks - Champion AI-first workflows with Claude Code, Cursor and similar tools (60-70% AI-assisted velocity) THE BUILDER MINDSET - First-principles engineer: you question assumptions and design elegant solutions from the ground up - Outcome obsessed: success is client impact, not lines of code - AI-native practitioner: you use Claude Code, Cursor or Copilot daily and ask "what can AI do better?" before writing code REQUIREMENTS - Agentic AI engineering is a must: production experience with multi-agent workflows, tool use / function calling, agent orchestration, evaluation, and operations (observability, guardrails, latency and cost management). Prototype-only experience doesn't clear the bar. - Production experience with LLMs, embeddings, vector databases, RAG and agent frameworks - Experience shipping on Gemini Enterprise / Vertex AI and AWS Bedrock (or strong depth on one and the aptitude to pick up the other quickly) - Strong Python plus working knowledge of TypeScript/Node.js and React/Next.js - Deploying AI systems on AWS (Lambda, ECS, SageMaker, Bedrock) or GCP (Cloud Run, Vertex AI, Cloud Functions) - REST API design, webhooks, enterprise system integration and reliable data pipelines - Ability to explain complex AI concepts to non-technical stakeholders - Comfortable in client discovery sessions, solution design workshops and technical deep-dives EXPERIENCE - 2-6 years of software engineering, with at least 1 year focused on AI/ML applications - Built and deployed LLM-powered and agentic features that real users interact with, including deployment and operations - End-to-end feature experience, not just backend or frontend in isolation - Experience working directly with stakeholders in consulting, product companies or startups