{"id":2802687,"url":"https://alion.io/job/artizent-lead-aiml-engineer-aws-platform","title":"Lead AI/ML Engineer - AWS Platform","company":{"id":3801272,"name":"Artizent","domain":"artizent.com","url":"https://alion.io/company/artizent","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":"lead","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":25000,"max_usd":67000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":44},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"Claude","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"LLMOps","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-07-31T05:04:43Z","employer_posted_date":null,"last_verified_at":"2026-07-31T05:04:43Z","board_verified":false,"closed_at":null,"days_open":85,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":85},"description":"Job Summary : \n\nWe are looking for an experienced Lead AI/ML Engineer to design and build scalable AI/ML solutions using AWS SageMaker, Amazon Bedrock, RAG architectures, and AI agents. \n\nThe ideal candidate should have strong hands-on experience in designing data foundations for AI workloads, integrating foundation models, and fine-tuning AI/ML solutions for enterprise use cases.\n\nKey Responsibilities : \n\n- Design and develop robust data foundations to support AI/ML workloads using Amazon SageMaker and Amazon Bedrock.\n\n- Architect and implement Retrieval-Augmented Generation (RAG) solutions for enterprise AI applications.\n\n- Design scalable and production-ready AI/ML pipelines and infrastructure on AWS.\n\n- Work with Amazon Bedrock foundation models and implement effective model integration strategies.\n\n- Develop and integrate AI agents using Agent Core and related agentic AI capabilities.\n\n- Implement and optimize Claude-based AI solutions, ensuring effective model integration and performance.\n\n- Identify suitable AI/ML workloads and use cases based on business requirements and technical feasibility.\n\n- Fine-tune and optimize AI/ML models to improve accuracy, performance, latency, and cost efficiency.\n\n- Evaluate different foundation models and AI/ML approaches and recommend the most appropriate solutions.\n\n- Develop scalable architectures for LLM, Generative AI, and agentic AI applications.\n\n- Work closely with data engineering, software engineering, cloud, and business teams to translate requirements into AI/ML solutions.\n\n- Establish best practices around model evaluation, prompt engineering, RAG performance, security, governance, and responsible AI.\n\n- Monitor AI/ML solutions in production and continuously identify opportunities for optimization and improvement.\n\n- Provide technical leadership, conduct architecture reviews, and mentor team members on AI/ML and Generative AI technologies.\n\nRequired Skills & Experience : \n\n- Strong experience in AI/ML engineering and solution architecture.\n\n- Hands-on experience with AWS SageMaker and Amazon Bedrock.\n\n- Strong understanding of Generative AI, Large Language Models (LLMs), and RAG architectures.\n\n- Experience working with Agent Core / agentic AI frameworks.\n\n- Strong experience integrating and working with Claude models.\n\n- Experience with AI/ML model fine-tuning, optimization, and evaluation.\n\n- Strong understanding of data pipelines and data foundations required for AI/ML workloads.\n\n- Experience designing scalable and production-ready AWS-based AI/ML architectures.\n\n- Strong programming skills in Python.\n\n- Experience with vector databases, embeddings, semantic search, and knowledge retrieval is highly desirable.\n\n- Understanding of MLOps/LLMOps, model monitoring, deployment, and lifecycle management.\n\n- Strong knowledge of cloud security, data privacy, and governance principles for AI/ML workloads.\n\nLeadership & Soft Skills : \n\n- Strong technical leadership and architecture capabilities.\n\n- Ability to evaluate emerging AI technologies and translate them into practical business solutions.\n\n- Excellent problem-solving and analytical skills.\n\n- Strong communication and stakeholder-management abilities.\n\n- Ability to mentor engineers and drive engineering best practices.\n\nKey Technologies : \n\n- AWS : SageMaker, Amazon Bedrock\n\n- GenAI : LLMs, RAG, Agentic AI, Claude\n\n- AI/ML : Model Fine-Tuning, Model Evaluation, MLOps/LLMOps\n\n- Programming : Python\n\n- Architecture : AI/ML Data Foundations, RAG Architecture, AI Agents\nSkills\nArtificial Intelligence, Machine Learning, RAG, AWS, AWS Bedrock, LLM, Agentic AI, Generative AI, Python, VectorDB","description_format":"text","description_chars":3655,"description_truncated":false,"requirements":{"experience_years_min":8,"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":["AI Consulting & 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