{"id":2805390,"url":"https://alion.io/job/cloudthat-genai-ai-ml-engineer","title":"GenAI / AI-ML Engineer","company":{"id":2540181,"name":"CloudThat","domain":"cloudthat.com","url":"https://alion.io/company/cloudthat","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"C","score":57,"open_postings":76,"ghost_share":0.711,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-21T05:46:15Z"}},"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":null,"salary_estimate":{"min_usd":38000,"max_usd":78000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"API Gateway","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Context Engineering","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"IAM","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"OpenSearch","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Tool Use","optional":false},{"name":"A2A","optional":true},{"name":"Amazon EKS","optional":true},{"name":"CI/CD","optional":true},{"name":"Computer Vision","optional":true},{"name":"Docker","optional":true},{"name":"Fine-tuning","optional":true},{"name":"GraphRAG","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"LoRA","optional":true},{"name":"MLFlow","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"Multimodal AI","optional":true},{"name":"NLP","optional":true},{"name":"PEFT","optional":true},{"name":"PyTorch","optional":true},{"name":"QLoRA","optional":true},{"name":"TensorFlow","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-09-07T17:04:41Z","employer_posted_date":"2026-09-07","last_verified_at":"2026-10-21T05:07:52Z","board_verified":true,"closed_at":null,"days_open":43,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":43},"description":"Role summary\nWe are seeking an experienced GenAI / AI-ML Engineer to design, build, deploy and operate production-grade AI/ML and Generative AI solutions on AWS. The role requires strong Python engineering, solid understanding of conventional machine-learning algorithms, practical experience with LLMs, RAG and agentic AI, and strong hands-on expertise with AWS AI/ML and Generative AI services.\nThe engineer will be responsible for taking AI solutions from problem definition and solution design through development, evaluation, production deployment and optimization. The candidate should be capable of making architecture and technology decisions based on scalability, latency, reliability, security, model quality and cost.\nThe role also requires a strong understanding of LLM token consumption, model pricing and AWS service/infrastructure costing, with the ability to design solutions that balance business requirements, technical performance and operational cost.\nKey responsibilities\nTranslate business problems into measurable AI/ML and Generative AI objectives, solution approaches and evaluation criteria.\nDesign and implement production-grade LLM, RAG, conversational AI and agentic AI solutions on AWS.\nBuild RAG pipelines including document ingestion, chunking, embeddings, metadata filtering, vector retrieval, reranking and generation.\nDesign and implement Amazon Bedrock Agents and Bedrock AgentCore-based agentic solutions, including tool use, memory/state, runtime execution and orchestration as applicable.\nWork with Amazon Bedrock foundation models and evaluate models based on quality, latency, token consumption and cost.\nBuild integrations between LLMs/agents and enterprise APIs, databases, applications, tools and knowledge sources.\nDevelop and evaluate supervised, unsupervised and deep-learning models based on business requirements.\nApply appropriate machine-learning algorithms for classification, regression, clustering, anomaly detection and other relevant use cases.\nPerform data preprocessing, feature engineering, model training, validation, hyperparameter tuning and error analysis.\nUse Amazon SageMaker for appropriate ML development, training, experimentation, deployment and model lifecycle requirements.\nEstablish evaluation mechanisms for LLM response quality, retrieval quality, groundedness, hallucination, latency and cost.\nAnalyze and optimize LLM input/output token consumption, context size and model selection to control GenAI costs.\nEstimate and optimize AWS infrastructure and service costs across model inference, compute, storage, APIs, vector search and other components.\nDesign end-to-end AWS architectures using appropriate managed AI/ML, compute, data, integration and security services.\nImplement security, access control, logging, monitoring, observability and operational controls for production AI systems.\nDeploy and operate AI/ML solutions on AWS and troubleshoot latency, scalability, reliability, model quality, infrastructure and cost issues.\nMonitor deployed ML models for performance, drift, reliability and business-aligned metrics.\nCollaborate with data engineers, software engineers, architects and product teams to build reliable production solutions.\nProduce reusable components, technical documentation, architecture decisions and implementation guidance for delivery teams.\nRequired qualifications and experience\n5+ years of relevant experience in AI/ML engineering, machine learning, Generative AI, applied data science or software engineering.\nStrong hands-on Python development experience with good understanding of object-oriented design, API integration, debugging and production engineering.\nDemonstrable experience taking AI/ML or GenAI solutions from POC/experimentation through production deployment.\nMandatory hands-on AWS experience implementing and deploying AI/ML or GenAI solutions.\nStrong hands-on experience with Amazon Bedrock and foundation models.\nHands-on experience with Amazon Bedrock AgentCore and/or Bedrock Agents for agentic AI solutions.\nHands-on experience with Amazon SageMaker for ML model development, training, deployment or lifecycle management.\nExperience with AWS services supporting GenAI architectures, including Amazon S3, Amazon OpenSearch Service/Serverless, AWS Lambda, API Gateway, Step Functions, CloudWatch, IAM, KMS and Secrets Manager.\nStrong understanding of LLMs, embeddings, vector search, prompt/context engineering and RAG.\nWorking experience with agentic AI, tool/function calling, agent orchestration and state management.\nStrong understanding of conventional machine-learning algorithms, model evaluation and statistical reasoning.\nAbility to select appropriate algorithms, models and AWS services based on the business problem.\nStrong understanding of trade-offs between model quality, accuracy, latency, scalability, reliability and cost.\nUnderstanding of LLM token economics, including input/output tokens, context consumption and model pricing.\nAbility to understand and estimate AWS service/infrastructure costs for an AI/ML solution.\nAbility to translate business requirements into secure, scalable, maintainable and cost-effective AWS AI/ML architectures.\nMandatory Skills\nPython, Pandas, NumPy, Scikit-learn\nConventional ML - Classification, Regression, Clustering, Anomaly Detection\nFeature Engineering, Model Training & Evaluation\nCross-validation, Hyperparameter Tuning, Error Analysis\nAWS - Bedrock, SageMaker, Knowledge Bases, OpenSearch/OpenSearch Serverless\nRAG, Embeddings, Vector Retrieval\nAgentic Workflows, Tool/Function Calling, State Management\nLLM Evaluation, Groundedness, Hallucination Mitigation\nLLM Token Consumption & Cost Estimation\nAWS Service/Infrastructure Cost Estimation & Optimization\nGood-to-Have Skills\nDocker, CI/CD, Kubernetes/EKS\nMLflow / SageMaker MLflow\nPyTorch/TensorFlow\nAdvanced MLOps & Model Monitoring\nFine-tuning, PEFT, LoRA, QLoRA\nAdvanced NLP, Computer Vision, Forecasting\nBedrock Agents / AgentCore\nMultimodal GenAI\nVoice AI / Conversational AI\nGraphRAG / Knowledge Graphs\nBedrock Guardrails / Evaluation\nMCP / A2A & Agent Interoperability\nAdvanced LLM Observability & Evaluation\nAdvanced Multi-Agent Architectures","description_format":"text","description_chars":6193,"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":["Information Technology","Professional Services","Cloud Consulting & Migration"],"lifecycle":[{"event":"open","at":"2026-10-18T05:07:51Z"}],"visa":[],"liveness":{"score":23,"band":"cold","label":"Long shot","p_open":1,"p_active":0.508,"p_room":0.45,"age_days":43,"expected_fill_days":28,"reasons":["conf:0","stale_co","velocity","win:tail"],"computed_at":"2026-10-21T05:46:15Z"},"pay":null,"html_url":"https://alion.io/job/cloudthat-genai-ai-ml-engineer","json_url":"https://alion.io/job/cloudthat-genai-ai-ml-engineer.json","meta":{"generated_at":"2026-10-21T08:49:44Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":12426,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-22T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":2540181},"rest":"https://alion.io/mcp/rest/get_company?id=2540181"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fcloudthat-genai-ai-ml-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fcloudthat-genai-ai-ml-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fcloudthat-genai-ai-ml-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/cloudthat-genai-ai-ml-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fcloudthat-genai-ai-ml-engineer"}]}