What are the responsibilities and job description for the Senior Fullstack AI Engineer position at Relanto?
Responsibilities:
- Design, develop, and deploy end-to-end AI-powered applications using React, Python, FastAPI, and AWS services.
- Build responsive and scalable frontend applications using React and optionally Next.js, ensuring seamless user experiences for AI-driven workflows.
- Develop backend APIs and microservices using Python and FastAPI to support AI and business application requirements.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, embedding generation, retrieval optimization, and response orchestration.
- Implement and integrate Model Context Protocol (MCP) servers and clients to enable secure communication between AI systems, tools, and enterprise applications.
- Build and maintain AI agent workflows leveraging Amazon Bedrock, foundation models, and agent orchestration frameworks.
- Integrate with LLM providers and Bedrock foundation models while implementing prompt engineering, tool calling, structured outputs, and reasoning workflows
- Design and implement vector database integrations and semantic search capabilities to support enterprise knowledge retrieval use cases.
- Develop real-time AI experiences using streaming APIs, Server-Sent Events (SSE), and WebSocket-based architectures
- Collaborate with product managers, architects, and business stakeholders to translate requirements into scalable AI solutions.
- Implement security, authentication, authorization, and observability best practices across AI applications and APIs.
- Participate in architecture reviews, code reviews, and technical design discussions while contributing to engineering best practices.
Required Skills:
- 5 years of software engineering experience with strong full-stack development expertise.
- Strong hands-on experience with React and modern JavaScript/TypeScript development.
- Experience with Next.js for server-side rendering and modern web application development (preferred but not mandatory)
- Strong proficiency in Python and backend development using FastAPI.
- Experience designing and implementing Retrieval-Augmented Generation (RAG) systems in production environments.
- Hands-on experience with Model Context Protocol (MCP), including MCP clients, servers, tools, and integrations.
- Strong knowledge of Amazon Bedrock and foundation model integrations.
- Experience working with LLMs such as Claude, Llama, Amazon Nova, Mistral, OpenAI, or similar models
- Experience implementing vector databases and semantic search solutions using technologies such as Pinecone, Weaviate, Chroma, or FAISS.
- Strong understanding of prompt engineering, tool calling, agent orchestration, and AI application architectures
- Experience developing REST APIs, microservices, and event-driven architectures.
- Familiarity with AWS services including Bedrock, Lambda, API Gateway, S3, DynamoDB, ECS/EKS, CloudWatch, IAM, and Secrets Manager.
- Experience with Docker, containerized deployments, and CI/CD pipelines.
- Strong understanding of authentication and authorization mechanisms including JWT, OAuth, and OIDC.
- Excellent problem-solving, communication, and collaboration skills.