{"id":4160301,"url":"https://alion.io/job/optimum-solutions-senior-genai-application-engineer","title":"Senior GenAI Application Engineer","company":{"id":3800114,"name":"Optimum Solutions","domain":"theoptimum.net","url":"https://alion.io/company/optimum-infosystem","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"contractor","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":8000,"max":10000,"currency":"SGD","period":"month","gross":true,"usd_annual":93420},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Docker","optional":false},{"name":"Function Calling","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"OpenShift","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false}],"status":"live","first_seen_at":"2026-11-12T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-11-12T00:00:00Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are seeking an experienced AI Engineer to design, develop and deploy production-grade Generative AI applications within an enterprise environment.\nThe successful candidate will have strong software Engineering fundamentals and hands-on experience with Large Language Models (LLMs), LangGraph, LangChain, Retrieval-Augmented Generation (RAG) and agenticAI workflows.\nThis role focuses on building scalable, reliable and maintainable GenAI applications, integrating AI capabilities with enterprise systems and delivering practical AI solutions for business users.\nKey Responsibilities\nDesign, develop and enhance production-grade Generative AI applications using frameworks such as LangGraph, LangChain or similar orchestration tools.\nBuild and implement Agentic AI workflows, Retrieval-Augmented Generation (RAG), tool calling, prompt orchestration and context management solutions.\nIntegrate Large Language Models (LLMs), including open-weight and hosted models, into enterprise applications and backend services.\nDevelop scalable backend services and REST APIs using Python, Java or other relevant programming languages.\nIntegrate GenAI applications with enterprise systems, databases, APIs, internal data sources and operational platforms.\nImplement production-level capabilities including logging, monitoring, tracing, evaluation, error handling and fallback mechanisms.\nWork with platform and infrastructure teams to deploy and maintain GenAI applications in containerized environments such as Kubernetes or OpenShift.\nTroubleshoot application issues, optimize performance and improve the reliability, scalability and maintainability of GenAI solutions.\nCollaborate with application, data, security, infrastructure and business teams to translate business requirements into practical AI solutions.\nEvaluate emerging GenAI technologies, frameworks and model-serving approaches to continuously improve application capabilities.\nRequirements\nMinimum 6 years of experience in software engineering, backend development or application engineering, with recent hands-on experience in GenAI application development.\nProven experience developing and deploying production-grade GenAI applications beyond prototypes, proof of concepts or experimental projects.\nStrong hands-on experience with LangGraph, LangChain or similar LLM orchestration frameworks.\nPractical experience in RAG, Agentic AI, tool calling, prompt engineering, prompt orchestration and context management.\nStrong understanding of Large Language Models (LLMs), including hosted models and open-weight models.\nProficiency in Python, Java or similar programming languages, with strong backend development capabilities.\nExperience developing and integrating REST APIs, backend services, enterprise applications and external data sources.\nGood understanding of distributed systems, application architecture, API design and production resilience patterns.\nExperience with application observability, logging, tracing, testing, debugging and performance optimization.\nFamiliarity with containerization and deployment technologies such as Docker, Kubernetes or OpenShift.\nSkills\nModel Serving, Debugging of Applications, Analysis of Data Sources, Generative AI Application Development and Deployment, Agent Orchestration, API Management, REST APIs development, Infrastructure Deployment, Computer Proficiency, Container Orchestration, Enterprise Applications, Reliability Improvement, Rest Apis, Orchestration, Solution Deployment, Error Handling","description_format":"text","description_chars":3502,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","IT Staffing & Staff Augmentation"],"lifecycle":[{"event":"open","at":"2026-11-12T11:22:51Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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