{"id":2966496,"url":"https://alion.io/job/daivtech-solutions-pvt-ltd-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":4455344,"name":"Daivtech Solutions Pvt Ltd","domain":"daivtech.com","url":"https://alion.io/company/daivtech-solutions-pvt-ltd","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":"senior","employment_type":"full_time","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":{"min":1000000,"max":2000000,"currency":"INR","period":"year","gross":true,"usd_annual":21132},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Django","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false},{"name":"Weaviate","optional":false},{"name":"Hugging Face","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Quantization","optional":true}],"status":"live","first_seen_at":"2026-10-20T10:14:20Z","employer_posted_date":null,"last_verified_at":"2026-10-20T10:14:20Z","board_verified":false,"closed_at":null,"days_open":7,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":7},"description":"Job Title: Senior AI Engineer\nExperience: 5–10 years in software engineering, with 3+ years in AI/ML engineering preferred\nEmployment Type: Full-time\nDepartment: Artificial Intelligence / Engineering\nLocation: Bangalore\n\nWe are looking for a highly skilled Senior AI Engineer to design, develop, deploy, and scale intelligent AI-powered applications and solutions. The ideal candidate will have strong expertise in machine learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and production-grade software engineering.\nThe candidate will work closely with product managers, data scientists, software engineers, and business stakeholders to translate complex business requirements into scalable, reliable, secure, and cost-effective AI solutions.\nKey Responsibilities\n1. AI Solution Design and Development\nDesign, develop, and deploy end-to-end AI and machine learning solutions.\nBuild intelligent applications using LLMs, Generative AI, NLP, and deep learning techniques.\nDevelop scalable AI architectures and reusable components for enterprise applications.\nEvaluate AI models and select appropriate approaches based on accuracy, latency, cost, and business requirements.\n2. Generative AI and LLM Engineering\nDevelop LLM-powered applications using models from providers such as OpenAI, Anthropic, Google, or open-source ecosystems.\nDesign and implement RAG pipelines, document processing workflows, semantic search, and knowledge retrieval systems.\nBuild AI agents and multi-step workflows using appropriate orchestration frameworks.\nImplement prompt engineering, structured outputs, tool calling, and context management.\nOptimize model performance through evaluation, fine-tuning where appropriate, and inference optimization.\n3. Machine Learning and Data Engineering\nDevelop and operationalize machine learning models for classification, prediction, recommendation, and other business use cases.\nWork with structured, unstructured, and multimodal data.\nBuild data preprocessing, feature engineering, model training, and validation pipelines.\nApply appropriate model evaluation techniques and statistical methods.\n4. Production Deployment and MLOps / LLMOps\nDeploy AI solutions using cloud platforms such as AWS, Microsoft Azure, or Google Cloud.\nBuild automated CI/CD pipelines for AI applications and model deployment.\nImplement model versioning, experiment tracking, monitoring, and performance evaluation.\nOptimize inference latency, throughput, infrastructure utilization, and operating costs.\nEstablish observability for AI applications, including token usage, retrieval quality, latency, failures, and model behavior.\n5. Software Engineering and System Architecture\nDevelop production-quality applications and APIs using Python and modern backend frameworks.\nDesign RESTful APIs, asynchronous processing systems, and microservices where appropriate.\nIntegrate AI services with enterprise applications, databases, and third-party systems.\nUse relational databases, vector databases, caching, and distributed systems effectively.\nApply software engineering best practices, including testing, code reviews, documentation, and design patterns.\n6. Security, Quality, and Responsible AI\nImplement safeguards against prompt injection, data leakage, insecure tool execution, and unauthorized access.\nApply appropriate privacy, security, and compliance controls to AI systems.\nEvaluate hallucinations, bias, reliability, and failure modes.\nDesign human-in-the-loop workflows and fallback mechanisms for critical use cases.\n7. Technical Leadership and Collaboration\nLead technical design discussions and mentor junior AI engineers.\nDefine engineering standards, coding practices, and AI development guidelines.\nCollaborate with cross-functional teams to deliver measurable business outcomes.\nConduct code reviews, evaluate emerging technologies, and recommend practical innovations.\nCommunicate technical trade-offs and solution architecture to both technical and non-technical stakeholders.\nRequired Technical Skills\nProgramming and Backend Development\nStrong proficiency in Python.\nExperience with FastAPI, Flask, or Django.\nKnowledge of REST APIs, asynchronous programming, data structures, algorithms, and software design principles.\nExperience with Git, automated testing, and CI/CD.\nAI and Machine Learning\nStrong understanding of supervised and unsupervised learning, model evaluation, and statistical concepts.\nHands-on experience with PyTorch, TensorFlow, or scikit-learn.\nKnowledge of NLP, embeddings, transformers, and deep learning fundamentals.\nGenerative AI and LLMs\nHands-on experience building production applications using LLM APIs or open-source models.\nStrong understanding of RAG architecture, embeddings, chunking, reranking, and retrieval evaluation.\nExperience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or pgvector.\nFamiliarity with orchestration frameworks such as LangChain, LangChain, or comparable tools.\nExperience with tool calling, structured generation, agent workflows, and LLM evaluation.\nCloud and Infrastructure\nExperience with AWS, Azure, or Google Cloud.\nWorking knowledge of Docker and Kubernetes.\nFamiliarity with model serving, scalable APIs, monitoring, and production deployments.\nExperience with MLOps or LLMOps practices.\nDatabases and Data Processing\nStrong SQL skills and experience with relational databases.\nFamiliarity with NoSQL databases, data pipelines, and distributed processing.\nExperience working with unstructured data, document ingestion, and retrieval systems.\nPreferred Qualifications\nExperience with fine-tuning, quantization, or serving open-source LLMs.\nExperience with multimodal AI, including text, image, audio, or video.\nKnowledge of agent evaluation, workflow orchestration, and multi-agent systems.\nExperience with AI security, guardrails, governance, and responsible AI.\nExperience optimizing AI workloads for latency, scalability, and cost.\nContributions to open-source AI projects, research, or technical publications.\nEducation\nBachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.\nEquivalent practical experience and demonstrated engineering expertise may be considered.\nKey Success Metrics\nQuality, accuracy, and reliability of deployed AI solutions.\nProduction adoption and measurable business impact.\nReduction in inference costs and response latency.\nRAG retrieval quality and reduction in unsupported or incorrect responses.\nSystem availability, scalability, and operational stability.\nDelivery timelines, code quality, and technical mentoring effectiveness.\nSkills\nFlask, Django, FastAPI, PyTorch, TensorFlow, Natural Language Processing (NLP), Hugging Face Transformers, embedding, Deep Learning, Information architecture, Pinecone, Weaviate, Qdrant, Milvus, Support vector machine, LangChain, MLOps, LLMOps","description_format":"text","description_chars":6936,"description_truncated":false,"requirements":{"experience_years_min":5,"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":[],"lifecycle":[{"event":"open","at":"2026-10-21T00:22:00Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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