AI full Stack Engineer (LLM) l 12-month contract

Responsibilities:Take ownership of an existing AI-powered application through structured knowledge transfer, including understanding and documenting architecture, codebase, and integrationsProvide ongoing application support including bug fixing, enhancements, incident resolution, performance tuning, and stability improvementsDesign, develop, and deploy end-to-end AI applications using LLMs, RAG, and agentic frameworksBuild MCP-based tool integrations and agentic workflows to connect AI solutions with enterprise systems and processesTranslate business requirements into scalable AI-powered solutions with robust backend and frontend designDevelop and integrate APIs, application logic, and user-facing features for AI-driven use casesImplement monitoring, observability, and evaluation mechanisms for AI models, prompts, and agent behaviorCollaborate with cross-functional stakeholders to deliver production-ready solutions aligned with business outcomesContribute to application design, code quality, testing, CI/CD, and engineering best practicesRequirementsBachelor’s degree in Computer Science or a related disciplineMinimum 2 years of experience in full stack software engineering with production application exposureProven experience building AI agents or multi-agent systems using frameworks like LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAIHands-on experience with LLMs, RAG architectures, agentic design patterns, and deploying generative AI applicationsFamiliarity with MCP integrations, AI guardrails, application evaluation, and LLMOps practicesUnderstanding of prompt engineering, model evaluation, AI observability tools (e.g., LangSmith), and responsible AISolid software engineering skills including clean code, testing, design patterns, REST APIs, CI/CD, and containerizationProficiency in Python, TypeScript, React / Next.js, and Tailwind CSSExperience with relational and NoSQL databases, including schema design and query optimizationFamiliarity with vector databases and semantic search for RAG applicationsHands-on experience with AWS services such as Lambda, API Gateway, S3, CloudWatch, and IAMExperience with AWS Bedrock, including foundation models, Knowledge Bases, Agents, and Guardrails