{"id":3089846,"url":"https://alion.io/job/robusta-mid-level-ai-developer-remote-3-months-octopus-by-rtg-immediate-hir","title":"Mid Level AI Developer - Remote - 3 Months - Octopus by RTG - Immediate Hir","company":{"id":94384,"name":"Robusta","domain":"robusta.tech","url":"https://alion.io/company/robusta-tech","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"HeadHunter","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["EG"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":76000,"max_usd":205000,"period":"year","method":"global_role_seniority_cell","sample_n":921},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS Strands Agents","optional":false},{"name":"Azure","optional":false},{"name":"Bicep","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"IAM","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Microsoft Entra ID","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Octopus Deploy","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Terraform","optional":false},{"name":"A2A","optional":true},{"name":"Databricks","optional":true},{"name":"Fine-tuning","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-22T11:09:33Z","employer_posted_date":null,"last_verified_at":"2026-10-22T11:09:33Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"We're looking for a MidLevel AI Developer to design, build and run production-grade agentic AI systems on AWS and Azure. You'll turn business problems into reliable multi-step agent workflows that use LLMs, tools and enterprise data. You'll own solutions from architecture and prototyping through deployment, evaluation and monitoring, and you'll set engineering standards for how we build with AI.\nWhat you will do\nDesign and build agentic AI systems: single and multi-agent workflows with planning, tool use, memory and human-in-the-loop controls.\n\nDevelop 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.\n\nBuild retrieval-augmented generation (RAG) pipelines, including data ingestion, chunking, embeddings, vector search and grounding over enterprise data.\n\nIntegrate agents with internal systems, APIs and SaaS tools, using standards such as the Model Context Protocol (MCP) and function/tool calling.\n\nImplement evaluation frameworks for quality, accuracy, safety and cost, including regression tests, LLM-as-judge methods and human review.\n\nAdd guardrails and responsible-AI controls: prompt-injection defences, content filtering, PII handling, access control and audit logging.\n\nContainerise and deploy services with CI/CD and infrastructure as code, and add observability (tracing, logging, latency and token-cost monitoring).\n\nOptimise performance, reliability and cost across models, prompts and infrastructure.\n\nMentor engineers, run design and code reviews, and document architectures and decisions.\n\nWork with product owners, data teams, security and architecture to take AI use cases from idea to production.\n\nRequirementsWhat you need to be successfulMust have\nBachelor's degree in Computer Science, Engineering or a related field (or equivalent experience).\n\n3+ years of software engineering experience, with 1+ years building LLM or GenAI applications in production.\n\nStrong Python skills, plus experience building and operating APIs and services.\n\nHands-on experience building agentic systems with a modern framework (for example LangGraph, LangChain, Microsoft Agent Framework / Semantic Kernel, AutoGen, Strands Agents or CrewAI).\n\nProduction experience on at least one of AWS or Azure AI services, and working knowledge of the other.\n\nPractical RAG experience with vector databases or search services (for example OpenSearch, Azure AI Search, pgvector or Pinecone).\n\nExperience with cloud fundamentals: containers (Docker, Kubernetes or serverless), networking and identity (IAM / Entra ID), and secrets management.\n\nExperience with CI/CD, Git and infrastructure as code (Terraform, Bicep or CloudFormation).\n\nUnderstanding of LLM evaluation, prompt engineering, and safety and security risks specific to AI systems.\n\nStrong communication skills and the ability to explain trade-offs to technical and non-technical stakeholders.\n\nNice to have:\nExperience with MCP servers, multi-agent protocols (for example A2A), or agent orchestration at scale.\n\nFine-tuning or model customization, and experience with 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