Mid Level AI Developer - Remote - 3 Months - Octopus by RTG - Immediate Hir

Overview

Design, build and run production-grade agentic AI systems on AWS and Azure, turning business problems into reliable multi-step agent workflows that use LLMs, tools and enterprise data.

What you'll do

• Design and build agentic AI systems: single and multi-agent workflows with planning, tool use, memory and human-in-the-loop controls.
• Develop LLM applications on AWS (Amazon Bedrock, Bedrock Agents/AgentCore) and Azure (Azure OpenAI, Microsoft Foundry / Azure AI Foundry), and recommend the right platform and model for each use case.
• Build retrieval-augmented generation (RAG) pipelines, including data ingestion, chunking, embeddings, vector search and grounding over enterprise data.
• Integrate agents with internal systems, APIs and SaaS tools, using standards such as the Model Context Protocol (MCP) and function/tool calling.
• Implement evaluation frameworks for quality, accuracy, safety and cost, including regression tests, LLM-as-judge methods and human review.
• Add guardrails and responsible-AI controls: prompt-injection defences, content filtering, PII handling, access control and audit logging.
• Containerise and deploy services with CI/CD and infrastructure as code, and add observability (tracing, logging, latency and token-cost monitoring).
• Optimise performance, reliability and cost across models, prompts and infrastructure.
• Mentor engineers, run design and code reviews, and document architectures and decisions.
• Work with product owners, data teams, security and architecture to take AI use cases from idea to production.

What you'll need

• Bachelor's degree in Computer Science, Engineering or a related field (or equivalent experience).
• 3+ years of software engineering experience, with 1+ years building LLM or GenAI applications in production.
• Strong Python skills, plus experience building and operating APIs and services.
• Hands-on experience building agentic systems with a modern framework (for example LangGraph, LangChain, Microsoft Agent Framework / Semantic Kernel, AutoGen, Strands Agents or CrewAI).
• Production experience on at least one of AWS or Azure AI services, and working knowledge of the other.
• Practical RAG experience with vector databases or search services (for example OpenSearch, Azure AI Search, pgvector or Pinecone).
• Experience with cloud fundamentals: containers (Docker, Kubernetes or serverless), networking and identity (IAM / Entra ID), and secrets management.
• Experience with CI/CD, Git and infrastructure as code (Terraform, Bicep or CloudFormation).
• Understanding of LLM evaluation, prompt engineering, and safety and security risks specific to AI systems.
• Strong communication skills and the ability to explain trade-offs to technical and non-technical stakeholders.

Nice to have

• Experience with MCP servers, multi-agent protocols (for example A2A), or agent orchestration at scale.
• Fine-tuning or model customization, and experience with open-source models.
• Background in a regulated sector such as banking, healthcare or government.
• Cloud certifications (for example AWS Certified AI Practitioner or Solutions Architect, Azure AI-102 or AZ-204, AZ-400).
• Experience with data engineering (Spark, Databricks, Fabric or Glue) and data governance.

Details

• Remote, 3-month engagement, immediate hire.