Head - AI Platform & Architecture in Jaipur, भारत

Senior AI Architecture Leader | AI-Native Enterprise PlatformReports to: CTO / Founding Team | Focus: Production AI platform | Employment: Full-time leadership roleRole Overview:The company is a technology firm based in Jaipur, India, building a next-generation, AI-native enterprise platform for the global maritime and shipping industry. Its first product is being developed for a leading Singapore-based shipping company, with stakeholders across Singapore, India, Europe, and the United https://jobeax.com/link/CZGPnthDVPoumdGg are looking for a senior, hands-on Head of AI Platform & Architecture to work with the CTO and founding team. This person will own the shared AI intelligence layer: design it, prove it in production, and build the specialist team. This is not an AI strategy, chatbot or prompt-engineering https://jobeax.com/link/iiA8WCpP3JMQaPrf Candidate Snapshot:Best-fit candidates have built production AI platforms at enterprise scale and can explain failures, trade-offs, governance and https://jobeax.com/link/p1vHdaS8gZYYOKrV Mission:- Create the shared AI foundation used by all enterprise modules, instead of isolated AI solutions by product team.- Build enterprise RAG, model orchestration/routing, agents, evaluations, observability, governance, security and AI cost controls.- Use AI to retrieve, reason and recommend while keeping authorization, business rules and irreversible actions under enterprise controls.- Define the cloud-versus-edge AI strategy for vessels, balancing accuracy, hardware, latency, connectivity, security and operating https://jobeax.com/link/K8alYFAPyzvLdvNZ Roles and Responsibilities:Platform Architecture:- AI platform architecture: Own the AI gateway, multi-model strategy, RAG, hybrid search, context management, agent orchestration, evaluations, observability and cost controls.- Enterprise knowledge and secure retrieval: Design permission-aware retrieval across manuals, procedures, work orders, maintenance history, operational records and governed enterprise https://jobeax.com/link/UYWhqEO8qQ1XokQi, Governance & Quality:- Agents, safety and oversight: Define controlled tool/API access, approval patterns, guardrails, auditability, and safe failure/abstention patterns.- AI quality and economics: Set test datasets, groundedness metrics, regression gates, model comparisons, latency targets, token budgets and cost monitoring.- AI-native product delivery: Partner with platform, backend and data teams so APIs, events, identity, permissions and knowledge are AI-consumable from Day https://jobeax.com/link/UdwKkJi6awpHd0jh & Leadership:- Team and engineering leadership: Stay hands-on early; recruit and mentor AI/LLM, AI platform and data/knowledge engineers; support responsible AI-assisted engineering https://jobeax.com/link/wJIgo45kO3tINlTo Candidate Profile:Must-Have Experience:- 10+ years in software or platform engineering, with recent ownership of production AI/ML/GenAI systems.- Hands-on architecture and delivery of enterprise LLM/GenAI platforms used by real users or business workflows.- Production RAG and knowledge systems with ingestion, metadata, retrieval quality, authorization-aware access and evaluation.- Agentic AI or controlled tool/API execution with authorization boundaries, failure handling and human approval.- Model selection and routing judgment across quality, latency, privacy, availability and inference cost.- AI evaluation and observability, including test sets, accuracy checks, regression testing, safety monitoring and feedback loops.- Cloud-native architecture, APIs, distributed systems, enterprise security and partnership with platform/data https://jobeax.com/link/gGZ45KjtHShBc6IF Preferred:- Reusable AI platform experience across multiple products or business domains.- Enterprise SaaS/ERP, regulated or safety-sensitive systems, multi-tenant, IoT/edge or intermittently connected environments.- Experience with major AI providers or open-source models; architecture judgment matters more than specific provider familiarity.- Practical exposure to local/edge model deployment and related hardware and operations trade-offs.- Zero-to-one product/platform experience in a founding, startup or transformation https://jobeax.com/link/RTQtAhBDm5Xe67BI Profile Summary:Target senior technology leaders who have built, operated and improved production AI systems not advisory-only or proof-of-concept https://jobeax.com/link/iTYwvU5rnEVOzXw2 Screening Guidance:- Prioritize candidates who can say: I built this, ran it in production, saw where it failed, and changed the https://jobeax.com/link/TaL5ArOM9wnbJBs1 Fit:- Principal/Staff AI architects, Heads of AI Platform, senior AI platform engineers, or engineering leaders with recent hands-on production https://jobeax.com/link/g2PY1rNOu2pZ7c6O Suitable:- AI strategy consultants, prompt engineers, chatbot-only developers, research-only profiles, or managers who cannot defend architecture and production failure modes. (ref:hirist.tech)