{"id":711263,"url":"https://alion.io/job/aisensy-ai-engineer","title":"AI Engineer","company":{"id":13319,"name":"Aisensy","domain":"aisensy.com","url":"https://alion.io/company/aisensy","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":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":49000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":32},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI 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Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"TensorFlow","optional":false},{"name":"Weaviate","optional":false},{"name":"Claude","optional":true},{"name":"Gemini","optional":true},{"name":"Llama","optional":true},{"name":"Mistral","optional":true},{"name":"PostgreSQL","optional":true},{"name":"TensorRT","optional":true},{"name":"TensorRT-LLM","optional":true},{"name":"TGI","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-09-11T04:51:39Z","employer_posted_date":null,"last_verified_at":"2026-09-11T04:51:39Z","board_verified":false,"closed_at":null,"days_open":46,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":46},"description":"The core responsibilities for the job include the following:\nAI Application Development:\nDesign, build, and deploy AI-powered applications using large language models, multimodal models, and intelligent agents.\nDevelop scalable AI solutions that automate enterprise workflows and enhance customer experiences.\nBuild reusable AI services, APIs, and components that integrate seamlessly into the platform.\nRapidly prototype, validate, and productionize AI use cases across multiple industries.\nLLM & Agent Engineering:\nDevelop advanced prompt engineering strategies, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows.\nBuild multi-agent systems capable of reasoning, planning, and executing complex enterprise tasks.\nIntegrate foundation models from leading providers while optimizing performance, reliability, and cost.\nEvaluate, fine-tune, and optimize AI models for production use cases.\nAI Platform Integration:\nIntegrate AI applications with enterprise systems, databases, APIs, and third-party platforms.\nBuild scalable inference pipelines and AI workflows that support production deployments.\nCollaborate with platform and infrastructure teams to optimize model serving, orchestration, and deployment.\nImplement robust evaluation frameworks to continuously measure AI quality and performance.\nPerformance & Reliability:\nOptimize AI applications for latency, accuracy, scalability, and operational efficiency.\nImplement observability, monitoring, logging, and evaluation pipelines for AI systems.\nEnsure AI solutions meet enterprise requirements for security, privacy, governance, and compliance.\nTroubleshoot production AI systems and continuously improve model performance through experimentation and feedback.\nEngineering Excellence:\nWrite clean, maintainable, and production-quality code following engineering best practices.\nConduct code reviews and contribute to technical design discussions.\nCollaborate closely with Product, Platform, Infrastructure, and Customer Success teams to deliver customer-centric AI solutions.\nStay current with emerging AI research, tools, and technologies, and evaluate their applicability to the platform.\nRequirements:\n3+ years of experience building AI, machine learning, or backend software applications.\nStrong proficiency in Python with experience building production-grade applications.\nHands-on experience with large language models, prompt engineering, Retrieval-Augmented Generation (RAG), and AI agent frameworks.\nExperience using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, LangGraph, or similar.\nFamiliarity with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or PGVector.\nExperience integrating AI applications with REST APIs, databases, and cloud services.\nUnderstanding of model evaluation, prompt optimization, hallucination mitigation, and AI quality measurement.\nExperience with Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.\nFamiliarity with Git, CI/CD pipelines, and software engineering best practices.\nUnderstanding of distributed systems, scalable APIs, and enterprise application development.\nExposure to fine-tuning, model serving, MLOps, or inference infrastructure is highly desirable.\nBonus/Good to Have:\nGenerative AI: Experience building enterprise applications using GPT, Claude, Gemini, Llama, Mistral, or other foundation models.\nAI Infrastructure: Experience with vLLM, TensorRT-LLM, TGI, model deployment, GPU optimization, or inference platforms.\nMachine Learning: Experience with supervised learning, deep learning, model training, evaluation pipelines, and ML frameworks such as PyTorch or TensorFlow.\nEnterprise Integrations: Experience integrating AI solutions with CRMs, ERPs, productivity tools, cloud platforms, and enterprise workflows.\nDeveloper Platforms: Experience building SDKs, APIs, developer tools, or AI platform capabilities for external developers.\nPreferred Attributes:\nFounder-level ownership and bias for action.\nStrong strategic thinking and ability to connect technical decisions to business impact.\nExcellent communication and 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