{"id":1993964,"url":"https://alion.io/job/manila-recruitment-agentic-ai-engineer","title":"Agentic AI Engineer","company":{"id":1582,"name":"Manila Recruitment","domain":"manilarecruitment.com","url":"https://alion.io/company/manila-recruitment","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":79,"open_postings":7,"ghost_share":0,"stale_share":0.857,"repost_share":0,"time_to_fill_p50_days":53,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mabalacat, Philippines"],"countries":["PH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"ASP.NET Core","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Hallucination","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"MLFlow","optional":false},{"name":"MS SQL","optional":false},{"name":"OCR","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"SharePoint","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TypeScript","optional":false},{"name":"Weaviate","optional":false},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-10-07T08:11:55Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-15T06:12:59Z","board_verified":true,"closed_at":null,"days_open":8,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":8},"description":"The Agentic AI Engineer will design, build and deploy production-grade AI solutions that improve productivity, decision-making and operational performance across the company’s Industries. You will also focus on large language models, agentic workflows, retrieval-augmented generation, business-system integrations and intelligent automation.\nCompany Profile:\nOur client is a wholly owned Australian company manufacturing a large range of steel products including Garden Sheds and Outdoor Buildings. From its manufacturing facility in Brisbane, our client distributes an extensive range of outdoor storage products throughout Australia, as well as exporting to the Pacific region and Europe. They have been a major supplier of outdoor storage products for over 55 years. The good reputation they have built is now being recognized throughout Australia and rapidly expanding to overseas markets including New Zealand and Europe.\nThis is an exciting opportunity to join a growing organisation that is investing in AI, e-commerce, and digital transformation. As an Agentic AI Engineer, you will work closely with technology and business teams to design, build, and deploy production-ready AI solutions, including LLM applications, RAG systems, and intelligent agent workflows. The role offers the opportunity to work on practical AI use cases that improve productivity, automate processes, connect business systems, and deliver measurable operational outcomes.\nDuties and Responsibilities:\nDesign, build and deploy LLM-powered applications and agentic AI workflows.\nDevelop AI agents capable of using approved tools and APIs, completing multi-step tasks and escalating decisions for human approval where required.\nBuild RAG solutions across structured and unstructured business information.\nDevelop document-ingestion, chunking, embedding, metadata, retrieval, reranking and response-grounding pipelines.\nIntegrate AI solutions with ERP, inventory, manufacturing, sales, finance, supply-chain and customer-service systems.\nBuild secure and maintainable APIs connecting AI applications with business systems and databases.\nMove solutions from proof of concept through testing, deployment, monitoring and ongoing production support.\nEstablish automated testing and evaluation for accuracy, retrieval quality, hallucination, latency, reliability and cost.\nImplement appropriate authentication, access controls, audit trails, guardrails and data-security protections.\nMonitor and optimise model usage, response times, infrastructure costs and overall system performance.\nMaintain clean, tested and well-documented Python code.\nWork with business stakeholders to convert operational problems into practical AI solutions.\nCollaborate closely with Absco’s Australian and Philippine teams.\nDocument architecture, APIs, deployment processes and support procedures.\nMonitor emerging AI technologies and recommend commercially valuable applications for the business.\nRequirements\nMust-have Skills / Qualification:\nAt least 2 years’ commercial experience building and deploying AI solutions.\nDemonstrated experience taking LLM, RAG or agentic AI solutions from experimentation through to production.\nStrong Python / C# .Net development skills.\nPractical experience with:\n- Large language models and LLM APIs\n- Agentic AI and multi-step workflows\n- Tool and function calling\n- Retrieval-augmented generation\n- Vector databases and semantic search\n- LangChain, LangGraph or comparable frameworks\n- REST APIs, webhooks and system integrations\n- Azure, AWS or Google Cloud Platform\nStrong SQL skills and experience working with structured and unstructured data.\nExperience building production APIs using FastAPI or similar frameworks.\nKnowledge of prompt design, structured outputs, response grounding and hallucination reduction.\nExperience with Git, automated testing, Docker, CI/CD and production monitoring.\nUnderstanding of AI security risks, including prompt injection, inappropriate data access and sensitive-information handling.\nAbility to communicate technical concepts clearly to non-technical stakeholders.\nStrong written and spoken English.\nAbility to work independently while collaborating effectively with a distributed team.\nStrong ownership and accountability from concept through to deployment.\nA practical and commercially focused approach to technology.\nCuriosity and a willingness to test and learn quickly.\nHigh standards for quality, security and reliability.\nComfort working through ambiguity and solving complex problems.\nA strong focus on delivering useful business outcomes, not demonstrations alone.\nClear communication and a collaborative working style.\nDiscipline in documenting systems and transferring knowledge.\nThe ability to balance delivery speed with appropriate engineering controls.\nAdvantageous but not required:\nDevelopment experience using ASP.NET, C#, .NET Core and Python, including integrating AI solutions with existing .NET applications and business systems.\nAzure OpenAI, Azure AI Foundry or the broader Microsoft technology environment.\nMicrosoft SQL Server, Microsoft 365, SharePoint, Microsoft Graph or Power Platform.\nExperience with pgvector, Pinecone, Qdrant, Weaviate or Azure AI Search.\nKnowledge of ERP, manufacturing, inventory, supply-chain, finance or customer-service systems.\nAI observability and evaluation tools such as LangSmith, Phoenix or MLflow.\nHuman-in-the-loop approval workflows and auditable agent actions.\nEvent-driven architecture, queues, background workers and workflow orchestration.\nOCR, document intelligence, speech transcription or computer-vision applications.\nFront-end development using React, TypeScript or similar technologies.\nExperience quantifying the commercial benefits of technology projects.","description_format":"text","description_chars":5765,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All 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