{"id":3827425,"url":"https://alion.io/job/ascendion-ai-solutions-engineer","title":"AI Solutions Engineer","company":{"id":46972,"name":"Ascendion","domain":"ascendion.com","url":"https://alion.io/company/ascendion","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":78,"open_postings":25,"ghost_share":0,"stale_share":0.88,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Solutions","role_family":"Solutions","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India","Hyderabad, India","Pune, India","Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":".NET","optional":false},{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"Hybrid Search","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"FHIR","optional":true},{"name":"HL7","optional":true},{"name":"LLMOps","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-10-26T13:08:32Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-07T19:26:10Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"Job Title: AI Solutions Engineer\nJob Type: Full-Time\nWork Mode: Hybrid (2/3 Days Office)\nLocation: Hyderabad, Bengaluru, Chennai, Pune\nExperience: 6 - 12 Years\nWorking Hours: 2 - 11 PM\nAbout the Role\nWe are seeking a highly skilled AI Solutions Engineer to architect, develop, and deploy enterprise-grade AI solutions using Generative AI, Large Language Models (LLMs), Python, .NET/C#, and Microsoft Azure Cloud as the primary technology stack. The ideal candidate will possess strong AI engineering expertise combined with modern software engineering capabilities to build scalable, secure, and production-ready AI applications.\nThis role requires hands-on experience designing and implementing LLM-powered applications, RAG solutions, Agentic AI systems, and cloud-native AI platforms. The successful candidate will be responsible for translating business requirements into enterprise AI architectures while owning the complete solution lifecycle from design and development through deployment, optimization, and production support.\nKey Responsibilities\nDesign, build, and deploy enterprise-scale AI applications using Python, .NET, C#, REST APIs, and Microservices. \nDevelop Generative AI, LLM, RAG, and Agentic AI solutions, including prompt engineering, tool/function calling, workflow orchestration, memory management, and multi-agent architectures.\nBuild and optimize retrieval pipelines encompassing document ingestion, chunking, embeddings, vector databases, semantic/hybrid search, reranking, and grounded response generation.\nLeverage Azure OpenAI, Azure AI Search, Azure AI Foundry, Azure AI Services, Azure Functions, and Azure App Services to deliver scalable cloud-native AI solutions.\nIntegrate AI capabilities with enterprise applications, APIs, databases, data platforms, and business workflows.\nDesign secure, resilient, and observable architectures utilizing CI/CD, automated testing, monitoring, logging, and performance optimization.\nTroubleshoot and optimize AI applications across prompts, LLMs, retrieval systems, agents, APIs, backend services, and cloud infrastructure.\nImplement Responsible AI, security, governance, and engineering best practices throughout the AI solution lifecycle.\nRequired Skills\nAI Engineering & GenAI\nStrong hands-on experience building and deploying production-grade AI applications.\nDeep expertise in Generative AI, Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), and Agentic AI.\nExperience designing and implementing Multi-Agent Systems and AI orchestration workflows.\nStrong understanding of LLM evaluation, context engineering, grounding techniques, hallucination mitigation, and Responsible AI practices.\nProgramming & Software Engineering\nStrong development experience with Python, .NET, and C#.\nExperience building enterprise applications using REST APIs, Microservices, and distributed architectures.\nExperience integrating AI services into enterprise-grade software platforms.\nAzure AI & Cloud\nHands-on experience with:\nAzure OpenAI Service\nAzure AI Search\nAzure AI Foundry\nAzure AI Services\nAzure Functions\nAzure App Services\nAzure DevOps\nExperience designing, deploying, and supporting AI workloads on Microsoft Azure Cloud.\nLLM & AI Frameworks\nHands-on experience with LangGraph, LangChain, Semantic Kernel, AutoGen, or similar orchestration frameworks.\nStrong expertise in embeddings, vector databases, semantic search, hybrid retrieval, metadata filtering, reranking, and retrieval optimization.\nExperience building conversational AI, copilots, intelligent assistants, and enterprise AI solutions.\nPlatform Engineering\nStrong understanding of SQL/NoSQL databases, Docker, containerization, cloud-native architectures, monitoring, and observability.\nExperience with CI/CD pipelines, automated testing, and production support.\nPreferred Skills\nExperience with MLOps, LLMOps, AI model evaluation, monitoring, and governance frameworks.\nExperience building enterprise-scale AI platforms with high availability, security, and scalability requirements.\nExposure to modern front-end technologies such as ReactJS or TypeScript is a plus.\n US Healthcare domain experience is desirable, including knowledge of Healthcare Payer/Provider ecosystems, Claims, Enrollment, Eligibility, Prior Authorization, Provider Data Management, FHIR/HL7 standards, and healthcare workflow modernization 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