{"id":2846471,"url":"https://alion.io/job/xilinx-junior-agentic-ai-software-development-engineer","title":"Junior Agentic AI Software Development Engineer","company":{"id":1764591,"name":"Xilinx","domain":"xilinx.com","url":"https://alion.io/company/xilinx-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":5400,"max":6000,"currency":"SGD","period":"month","gross":true,"usd_annual":56268},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Context Engineering","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Anthropic","optional":true},{"name":"AutoGen","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Chroma","optional":true},{"name":"CI/CD","optional":true},{"name":"CrewAI","optional":true},{"name":"Embeddings","optional":true},{"name":"Gemini","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Machine Learning","optional":true},{"name":"Milvus","optional":true},{"name":"OpenAI","optional":true},{"name":"OpenAI Codex","optional":true},{"name":"Pinecone","optional":true},{"name":"Rest API","optional":true},{"name":"Semantic Search","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-10-19T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-19T00:00:00Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"THE ROLE:\nWe are seeking a passionate and highly motivated AI Engineer to join our AI Engineering team focused on building the next generation of Agentic AI and Digital Agents. In this role, you will participate in the complete lifecycle of AI solution development, from prompt engineering and context engineering to deploying AI agents into real business environments. You will work alongside senior AI engineers, business stakeholders, and domain experts to build intelligent systems that automate workflows, enhance productivity, and transform enterprise operations.This is an excellent opportunity for early-career engineers who are excited about Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and enterprise AI deployment.\n\nTHE PERSON:\nHands-on experience building real-world Agentic AI systems\nExposure to enterprise-scale AI deployment and Digital Worker platforms\nMentorship from experienced AI engineers and architects\nOpportunities to work with cutting-edge LLM technologies and AI frameworks\nDirect involvement in AI transformation initiatives across multiple business functions\nCareer growth path toward AI Engineer, Senior AI Engineer, AI Architect, or Forward Deployment Engineer roles\n\nKEY RESPONSIBILITIES:\nAgentic AI Development\nDesign, develop, and test AI agents capable of multi-step reasoning and workflow execution\nBuild solutions leveraging LLMs, tool usage, memory, and agent orchestration frameworks\nImplement function calling, structured outputs, and automated workflows\nDevelop Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge sources\nOptimize AI system performance, reliability, scalability, and response quality\nAssist in evaluating and benchmarking AI model effectiveness\nPrompt & Context Engineering\nDesign effective system prompts and task-specific prompts\nBuild context retrieval and grounding strategies to improve AI accuracy\nDevelop methods to reduce hallucinations and improve consistency\nSupport the creation of evaluation frameworks and automated testing pipelines\nExperiment with prompting techniques, reasoning patterns, and agent behaviors\nForward Deployment Engineering (FDE)\nDeploy AI solutions into real business processes and operational environments\nIntegrate AI agents with APIs, databases, enterprise platforms, and business applications\nCollaborate directly with stakeholders to understand requirements and refine use cases\nMonitor deployed systems, troubleshoot issues, and implement enhancements\nGather feedback and continuously improve AI solutions based on business outcomes\nSoftware Engineering & Operations\nDevelop and maintain production-quality Python applications\nImplement logging, monitoring, testing, and observability practices\nParticipate in code reviews and engineering best practices\nSupport cloud deployment and containerized AI environments\nDocument technical solutions and operational procedures\n\nPREFERRED EXPERIENCE:\nStrong Python programming skills\nUnderstanding of APIs, JSON, REST services, and software integration\nFamiliarity with machine learning and natural language processing fundamentals\nStrong analytical and structured problem-solving abilities\nAbility to learn quickly in a fast-paced and evolving AI environment\nStrong communication and collaboration skills\nOpenAI, Azure OpenAI, Anthropic, Google Gemini, or similar LLM platforms\nBuilding LLM applications, chatbots, copilots, or AI assistants\nRetrieval-Augmented Generation (RAG) architectures\nVector databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search\nAgent frameworks including LangChain, LangGraph, CrewAI, LlamaIndex, AutoGen, or Semantic Kernel\nFunction calling, embeddings, semantic search, and context management\nPrompt engineering and AI evaluation methodologies\nCloud platforms such as Azure, AWS, or Google Cloud\nDocker, Kubernetes, CI/CD pipelines, or DevOps practices\nGit, software testing, and modern development workflows\nCurious and passionate about AI innovation\nStrong ownership mentality with a willingness to experiment\nCustomer-focused mindset and ability to work directly with users\nComfortable navigating ambiguity and solving complex problems\nTeam player who thrives in a collaborative environment\nEager to build AI systems that deliver measurable business impact\n\nACADEMIC CREDENTIALS:\nDegree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or a related technical field\n\nLOCATION:\nSingapore\nSkills\nChatbot, Natural Language Understanding, Ai, JSON, Design, Scalability, Pipelines, Interpersonal Skills, Azure OpenAI, Tool Design, OpenAI Codex, AI Evaluation, Analytical and Problem-Solving Skills, Rest Apis, Programming, Workflow Solutions","description_format":"text","description_chars":4713,"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":[]},"benefits":[],"hiring_locations":[{"name":"Singapore","iso":"SG","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips"],"lifecycle":[{"event":"open","at":"2026-10-19T10:30:16Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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