AI Evangelist / Sr AI Engineer

DataJobs; San Antonio (TX); On-site; USD 400,000 - 5,000,000; Full time

Job summary

Yamaha Motor Solutions India seeks an experienced AI Evangelist & Core AI Engineer to design, build, deploy, and scale enterprise-grade AI solutions. You will work hands-on across LLMs, RAG architectures, and agentic AI while guiding teams on responsible AI adoption throughout the SDLC.

The role emphasizes reliability, governance, security, cost optimization, and observability, with onsite work in San Antonio, TX and collaboration across cloud, security, and enterprise-architecture teams.

Qualifications

• 8+ years of experience in AI/ML engineering and related fields.
• Strong background in AI, ML, DL, and enterprise AI solutions.
• Experience with AI platforms and AI techniques, including Azure Cognitive Services.

Responsibilities

• Design, develop, and implement enterprise-grade AI and Generative AI applications.
• Architect scalable AI platforms and agent frameworks for enterprise use cases.
• Collaborate with cloud, security, EA, DevOps and engineering teams to deliver production solutions.

Skills

AI engineering

Machine Learning

Artificial Intelligence

Deep Learning

Neural Networks

LLM/SLM

RAG

MLOps

LLMOps

GenAIOps

Education

BE/BTech

Tools

Azure Cognitive Services

Job description

Yamaha Motor Solutions India is seeking a highly experienced AI Evangelist & Core AI Engineer to design, build, demonstrate, deploy, and scale enterprise-grade AI and Generative AI solutions. This onsite role is focused on hands-on AI engineering across LLM and agentic AI, RAG architectures, and scalable enterprise integration, while also helping teams understand practical, responsible AI opportunities.

What you’ll deliver

You will build and advance AI platforms and applications that can support enterprise-scale workloads, with a strong emphasis on reliability, security, performance, observability, cost optimization, and governance. Alongside delivery, you will act as an internal champion who accelerates responsible AI adoption throughout the Software Development Life Cycle.

Key responsibilities

• Design, develop, and implement enterprise-grade AI and Generative AI applications.
• Build scalable LLM-based applications using tools such as LLMs, multimodal models, AI agents, RAG, vector databases, knowledge graphs, APIs, and enterprise data platforms.
• Architect solutions for enterprise-scale workloads with considerations for scalability, reliability, security, performance, observability, cost optimization, and governance.
• Develop advanced RAG architectures, including hybrid search, reranking, metadata filtering, semantic retrieval, and knowledge grounding.
• Build multi-agent and agentic AI applications for reasoning, tool usage, workflow execution, orchestration, and enterprise system integration.
• Integrate structured and unstructured enterprise information into AI applications.
• Evaluate architecture tradeoffs across commercial models, open-source models, small language models, domain-specific models, and hosted AI platforms.
• Implement model routing, prompt orchestration, caching, guardrails, evaluation pipelines, and fallback strategies.
• Collaborate with cloud, platform, security, enterprise architecture, DevOps, and application engineering teams to deliver production solutions.
• Design scalable LLM platforms supporting multiple enterprise applications and use cases, including reusable LLM services, APIs, components, agent frameworks, and reference architectures.
• Develop AI agents and agentic workflows that automate complex business and engineering processes, interacting with enterprise applications, APIs, databases, documents, development environments, and workflow platforms.
• Evaluate emerging agent architectures and orchestration frameworks pragmatically.
• Develop reusable patterns for single-agent, multi-agent, human-in-the-loop workflows, autonomous workflows, tool-calling agents, coding agents, and enterprise knowledge agents.
• Establish controls for AI agent identity, permissions, auditability, security, and human oversight.
• Drive adoption of AI across the Software Development Life Cycle, including prototyping and demonstrations before formal enterprise implementation.
• Experiment with emerging AI models, agents, frameworks, and architectures, and convert emerging technology into demonstrable business scenarios.
• Identify limitations and edge cases before solutions reach production, and feed technical learnings into enterprise architecture, product strategy, AI standards, and engineering practices.
• Act as a visible internal champion for responsible and effective AI adoption, educating engineering and business teams about practical AI opportunities and demonstrating emerging AI.

Core technologies you’ll work with

The ideal candidate will have strong conceptual and practical understanding across modern AI, including Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, LLM/SLM, RAG, Graph RAG, MLOps, LLMOps, and GenAIOps.

Requirements

• 8+ years of experience (Above 8 years)
• Education: BE/BTech
• Strong background across: Machine Learning, Artificial Intelligence, Deep Learning, and Artificial Intelligence engineering
• Experience relevant to AI engineering and AI solutions, including AI platform and AI techniques
• Exposure to Azure Cognitive Services

Role details

• Location: San Antonio, TX (onsite)
• Department: ETI
• Open positions: 1
• Salary range: USD 400,000 - 5,000,000 per year
• Posted on: 17-Sep-2026
• Key responsibilities focus areas: Core AI Engineering & Architecture; Deep AI / ML / DL Expertise; Generative AI & LLM Engineering; AI Agents & Automation; AI-Enabled Software Engineering; Build Frontier AI Demonstrations; AI Evangelism & Enterprise Adoption