{"id":2786608,"url":"https://alion.io/job/syrencloud-seniorlead-ai-engineer","title":"Senior/Lead AI Engineer","company":{"id":4442673,"name":"Syren","domain":"syrencloud.com","url":"https://alion.io/company/syrencloud","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"SharePoint","optional":false}],"status":"live","first_seen_at":"2026-09-03T11:37:19Z","employer_posted_date":"2026-09-03","last_verified_at":"2026-10-18T08:12:24Z","board_verified":true,"closed_at":null,"days_open":44,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":44},"description":"Job Description - Senior/Lead AI Engineer\nPosition: Senior/Lead AI Engineer (Generative AI, RAG & Agentic AI)\nExperience: 5+ Years\nAbout the Role\nWe are seeking a talented and hands-on AI Engineer to join our growing AI team. The ideal candidate will have practical experience designing, developing, and deploying Generative AI solutions, Retrieval-Augmented Generation (RAG) applications, and Agentic AI systems. You will work on building intelligent assistants, autonomous workflows, enterprise knowledge platforms, and AI-powered business solutions, leveraging Large Language Models (LLMs).\nThis role requires strong Python development skills, expertise in AI frameworks such as LangChain and LangGraph, and the ability to build scalable production-grade AI applications.\nKey Responsibilities\nGenerative AI Development\nDesign, develop, and deploy AI-powered applications using Large Language Models (LLMs).\nBuild conversational AI assistants, copilots, and enterprise AI solutions.\nDevelop and optimize prompts, tools, and workflows to improve AI performance and accuracy.\nEvaluate and monitor AI model responses and implement guardrails for responsible AI usage.\nRAG Solution Development\nDesign and implement Retrieval-Augmented Generation (RAG) architectures.\nBuild document ingestion, indexing, embedding, and retrieval pipelines.\nIntegrate enterprise knowledge sources including databases, SharePoint, APIs, documents, and cloud storage.\nOptimize chunking, retrieval, reranking, and grounding strategies to improve answer quality.\nAgentic AI Development\nDesign and implement Agentic AI solutions using frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.\nBuild multi-agent workflows capable of planning, reasoning, tool usage, and task execution.\nIntegrate AI agents with enterprise applications, APIs, and business processes.\nDevelop memory management and workflow orchestration capabilities.\nSoftware Engineering & Integration\nDevelop scalable backend services using Python and FastAPI.\nBuild and consume REST APIs for AI integrations.\nImplement robust error handling, logging, monitoring, and performance optimization.\nCollaborate with architects, product owners, and business stakeholders to translate requirements into AI solutions.\nCloud & Deployment\nDeploy AI applications on Azure, AWS, or GCP.\nImplement CI/CD pipelines and DevOps best practices.\nMonitor 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