{"id":1449821,"url":"https://alion.io/job/simplify-hr-proprietary-limited-ai-engineer","title":"AI Engineer","company":{"id":1891733,"name":"Simplify HR","domain":"simplify.hr","url":"https://alion.io/company/simplify-hr","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":{"grade":"B","score":75,"open_postings":369,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-01T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["South Africa"],"countries":["ZA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":65000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":585},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A2A","optional":false},{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Amazon S3","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Copilot","optional":false},{"name":"Copilot Studio","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NLP","optional":false},{"name":"OCR","optional":false},{"name":"OpenAI","optional":false},{"name":"PoC Library","optional":false},{"name":"Power Apps","optional":false},{"name":"Power Automate","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"SQL","optional":false},{"name":"Tool Use","optional":false},{"name":"Vertex AI","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-06-24T00:00:00Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-09-29T13:23:43Z","board_verified":true,"closed_at":null,"days_open":99,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":99},"description":"We are recruiting a hands-on AI Engineer to design, build and operationalise cloud-based AI solutions across Microsoft Azure, AWS and Google Cloud. The role sits within the Data & Analytics team and reports into the AI Capability Lead, contributing to enterprise AI delivery primarily in Financial Services (Banking, Insurance, BaaS, Central Bank) with cross-sector work in Public Sector, Mining and Retail.\nThe successful candidate combines strong AI / Generative AI engineering with solid data engineering and MLOps foundations. They will deliver production-grade Generative AI, RAG agents, document intelligence and machine learning solutions on the hyperscalers, integrate them into client systems, and contribute to client engagements, demos, RFPs and the maturing of the firm's AI capability.\n\nRole Context & Reporting Line:\n\nReports to the AI Capability Lead (Data & Analytics).\nWorks as part of a multidisciplinary AI delivery team across multiple client business units.\nEngages senior stakeholders, SteerCo and (where appropriate) C-suite, Model Risk and Architecture Boards.\nSupports the build-out of the AI capability: partnerships with Microsoft, AWS, Google, Databricks and Anthropic; pre-sales support; PoC and production delivery on cloud AI solutions.\nKey Responsibilities:\nAI & Generative AI Engineering\nDesign, build and deploy Generative AI and LLM-based applications, including end-to-end RAG agents and agentic / multi-agent solutions.\nImplement RAG pipelines: chunking strategies, embeddings, dynamic indexing, vector databases, vector indexing, grounding and evaluation.\nBuild document intelligence solutions: OCR, classification, custom/neural extraction, table extraction and post-processing for unstructured data.\nImplement tool/function calling, prompt engineering, fine-tuning and guardrails for production AI agents.\nIntegrate AI models into enterprise systems via APIs, Service Bus, web apps and downstream platforms.\nExperience/knowledge of fine-tuning generative AI models, MCP, AI tool calling, A2A and graph databases.\nCloud AI Solution Delivery Proficient in any of the following (At least 1 CSP) (Azure | AWS | GCP)\nAzure: Azure OpenAI, AI Foundry / Prompt Flow, AI Search, Cognitive Services, Document Intelligence, Functions, Container Apps, Web Apps, Synapse, Data Lake, DevOps CI/CD.\nAWS: Amazon Bedrock (Anthropic/Claude, Titan Embeddings), Lambda, S3 data lakes, Textract and supporting services for AI agents and RAG.\nGCP: Vertex AI, Cloud Run, Google AppSheet and supporting services for AI workloads.\nMicrosoft Fabric & Power Platform: Copilot Studio, AI Builder, Power Apps, Power Automate for rapid AI / automation delivery.\nDatabricks: notebooks, ML workflows, Lakehouse and Generative AI capabilities.\nDesign and implement cloud AI architectures, including migration patterns across hyperscalers where required.\nData Engineering for AI (AI-Data Engineering)\nDesign and implement reliable data pipelines (Python, SQL, PySpark) to support ML and AI workloads.\nPrepare, transform and manage structured and unstructured data for AI use cases (ingestion, ETL/ELT, modelling, lakehouse).\nImplement chunking, embedding, indexing and retrieval mechanisms across vector stores.\nEnsure data quality, lineage and governance alignment, including Purview / catalog tooling where applicable.\nAIOps & Operationalisation\nBuild CI/CD pipelines for ML and AI models (Azure DevOps, GitHub Actions or equivalent).\nManage model deployment, monitoring, versioning and performance optimisation.\nImplement scalable, secure inference architectures (Container Apps, Lambda, Cloud Run, Functions).\nApply Responsible AI, model risk, security and compliance practices (RBAC, Key Vault / Secrets Manager, VNets / Private Endpoints, Monitor / Log Analytics).\nConsulting & Delivery\nEngage client stakeholders and translate business requirements into AI solution designs.\nContribute to discovery, design, estimation, costing and commercial models.\nCommunicate risks, trade-offs, model assumptions and limitations clearly to technical and business audiences.\nProduce solution architecture, status reports, SteerCo material, governance artefacts and user documentation.\nSupport pre-sales, demos, PoCs and RFP responses; contribute to the AI capability roadmap and uplift of junior engineers.\nRequired Skills & Experience:\nDegree in Computer Science, Data Science, Engineering, Mathematics or a related quantitative field.\n3+ years' experience delivering AI / ML / data solutions, ideally in a consulting or enterprise delivery environment.\n1-2+ years' hands-on Generative AI engineering experience (LLMs, RAG, embeddings, vector DBs, prompt engineering).\n3+ years' broader ML / AI delivery experience (supervised ML, feature engineering, evaluation, NLP).\nStrong data engineering: pipelines, Python / PySpark, data modelling, lakehouse patterns.\nCloud experience on at least one of Azure, AWS or GCP, with working knowledge of a second; containerisation and CI/CD.\nExperience integrating AI into enterprise systems via APIs, web apps and messaging.\nBusiness acumen: ability to link AI solutions to business value, ROI and risk.\nStrong communication, stakeholder management, collaboration and analytical skills.\nAdvantageous Certifications in Any of the following:\nCertifications - AWS (AI / ML & Architecture)\nAWS Certified AI Practitioner.\nAWS Certified Machine Learning - Specialty.\nAWS Certified Machine Learning Engineer - Associate.\nAWS Certified Solutions Architect (Associate or Professional).\nAWS Certified Data Engineer - Associate.\nCertifications - Microsoft Azure (AI & Data)\nMicrosoft Certified: Azure AI Engineer Associate (AI-102).\nMicrosoft Certified: Azure AI Fundamentals (AI-900).\nMicrosoft Certified: Azure Data Scientist Associate (DP-100).\nMicrosoft Certified: Fabric Analytics Engineer Associate (DP-600) or Fabric Data Engineer Associate (DP-700).\nMicrosoft Certified: Azure Data Engineer Associate (DP-203).\nMicrosoft Certified: Azure Solutions Architect Expert (AZ-305).\nMicrosoft Applied Skills credentials in Generative AI, Azure OpenAI, Semantic Kernel, Copilot, AI Builder or Document Intelligence.\nCertifications - Google Cloud (AI & Data)\nGoogle Cloud Certified - Professional Machine Learning Engineer.\nGoogle Cloud Certified - Generative AI Leader.\nGoogle Cloud Certified - Professional Data Engineer.\nGoogle Cloud Certified - Professional Cloud Architect.\nGoogle Cloud Certified - Cloud Digital Leader.\nCertifications - Other AI / Data Platforms\nDatabricks Certified Generative AI Engineer Associate.\nDatabricks Certified Machine Learning Associate / Professional.\nDatabricks Lakehouse Fundamentals / Data Engineer.\nAnthropic / Claude developer credentials.\nNVIDIA Deep Learning Institute (DLI) certifications in Generative AI or LLMs.\nHarvard or other recognised Data Science / Machine Learning credentials.\nOther Advantageous Experience\nMicrosoft Fabric, Azure AI Foundry, Azure OpenAI and solution delivery experience.\nAWS Bedrock with Anthropic Claude, Titan Embeddings and Textract in production.\nGCP Vertex AI and Cloud Run delivery experience.\nKnowledge graphs, advanced RAG patterns, agent orchestration and multi-agent frameworks.\nExposure to Model Risk Management (MRM), Architecture Review Boards and Responsible AI frameworks.\nExperience productising AI solutions and contributing to AI CoE / Target Operating Model design.\nTrack record in pre-sales, RFPs, technical demos and client workshops.\nSuccess Measures:\nProduction-grade AI solutions deployed across Azure, AWS and / or GCP.\nScalable, governed data and AI pipelines established and reused across engagements.\nMeasurable contribution to revenue, pre-sales and RFP wins.\nReduced time-to-production for new AI use cases through reusable patterns and accelerators.\nDemonstrable mentorship of junior engineers and uplift of the broader AI capability.\nHigh-quality stakeholder engagement, SteerCo and executive communication.\n Please Note:\nAs all iqbusiness roles require honesty in the handling of or access to cash, finances, financial systems, or confidential information; our recruitment process requires that the following background checks be completed: credit, criminal, ID, and qualification verification.\niqbusiness is committed to sustainable growth and transformation, we embrace diversity and employ previously disadvantaged individuals.","description_format":"text","description_chars":8362,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":true,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Professional Services","Human Resources","Recruiting Software & ATS"],"lifecycle":[{"event":"open","at":"2026-09-29T07:40:03Z"}],"liveness":{"score":10,"band":"cold","label":"Long shot","p_open":1,"p_active":0.357,"p_room":0.28,"age_days":99,"expected_fill_days":49,"reasons":["conf:40","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/simplify-hr-proprietary-limited-ai-engineer","json_url":"https://alion.io/job/simplify-hr-proprietary-limited-ai-engineer.json","meta":{"generated_at":"2026-10-01T09:50:51Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":658,"day_limit":5000,"remaining_today":4342,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}