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Principle Human Factors Engineer in India

234 active opportunities ยท Updated October 2026

Explore current principle human factors engineer jobs across India. Filter by work mode, employment type, experience, department, date posted and distance.

M
๐Ÿ“ Indiaยท Full-time
โœ“ Quality checkedCompany trend -100%

This role can be based remotely in India. Position Summary We are seeking an exceptional Principal Technologist to join our team in India. This pivotal role will work closely with our account teams to engage with C-suite executives and senior technical leaders at MongoDBโ€™s most strategic customers. You will bridge the gap between complex data architectures and AI to power business transformation, positioning MongoDB as the premier platform for modernizing legacy systems and building next-generation AI applications. As a recognized technical thought leader, you will shape industry perspectives through regular activities including high-impact technical evangelism and thought leadership, executive roundtables, presentations delivered to customers, keynotes at MongoDB and industry events, and regularly briefing tier-1 press, media, and analysts as a credible and trusted company spokesperson. Qualifications 10+ years of experience in customer and market-facing roles at the principal or Field CTO level Recognized technical leader with deep hands-on experience with enterprise-scale applications Influence & Scalability: Demonstrated success in scaling your technical influence and earned credibility. Experience speaking at major tech conferences, hosting technical webinars, or contributing deeply to the developer community (via technical blogs, open-source contributions, or whitepapers) is highly desired Deep portfolio and history of published content, presentations at events, interviews or quotes in the the press and media Executive Presence: Exceptional ability to command a room with credibility, deliver compelling keynote presentations, and influence technology strategies with a CxO audience Strong understanding of database architectures, distributed systems, and cloud computing concepts, with experience in distributed systems design, including scalability, fault tolerance, and consistency models Familiarity with modern application development frameworks and han

MongoDBAWSAzureGit
E(
๐Ÿ“ Indiaยท Full-time
โœ“ Quality checkedCompany trend -93.7%

About Ema Ema is building the worldโ€™s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production โ€” we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents โ€” spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation โ€” ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA

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