Senior Technical Trainer / Developer Advocate job opportunity at Ema Unlimited.

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Ema Unlimited Senior Technical Trainer / Developer Advocate
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Pattern: full-time
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Post sales

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degreeBachelor's (B.Sc.)
loacation India, India
loacation India....India

Product Instructor – Agentic AI Builder Location: Bangalore (Hybrid) About Ema Ema is redefining how work gets done by building the next generation of agentic AI technology that empowers every employee to be their most creative and productive. Our Universal AI Employee automates repetitive tasks, enabling enterprises to focus on strategic initiatives. Founded by ex-Google, Coinbase, and Okta executives and backed by the world’s top investors and angels, Ema is well-positioned to revolutionize enterprise productivity. We are headquartered in Silicon Valley, with a rapidly growing team in Bangalore. Our hybrid work environment encourages innovation and collaboration across geographies. Role Overview As a Senior Technical Trainer / Developer Educator (Product Instructor) for Ema’s Agentic AI Builder , you will lead the design and delivery of a world-class enablement program that helps customer engineering teams learn, build, deploy, and operate AI agents independently. This is not a traditional training role. You’ll blend strong technical depth (APIs, integrations, cloud, debugging, production operations) with instructional excellence to create structured training, hands-on labs, and certification frameworks that accelerate customer adoption and reduce long-term dependency on Ema. You will partner closely with Product Engineering, AI Application Engineering, Solution Architects, and SRE/DevOps to ensure enablement is accurate, practical, enterprise-ready, and continuously evolving with the Agentic AI Builder roadmap. Key Responsibilities 1. Training Enablement Program (Core Ownership) Own and evolve the role-based enablement curriculum for the Agentic AI Builder (Developer, Admin/Ops, Security/Compliance). Deliver instructor-led training (virtual/on-site), interactive workshops, and structured office hours. Create progressive learning paths that cover: Agentic AI Builder fundamentals and mental model (agents, tools, workflows, policies/guardrails) Builder UX + developer workflows (templates, debugging, testing) Integrations and enterprise connectivity (APIs, events, webhooks, connectors) Observability and quality (logs, traces, evaluation, prompt/agent debugging) Release lifecycle (environments, versioning, change management) Production readiness (reliability, scaling, incident response) 2. Hands-On Labs, Capstones, and Sample Assets Build and maintain hands-on labs, sample agent projects, reference implementations, and quickstart guides. Create capstone exercises that reflect real enterprise use cases (e.g., ticket triage, HR ops, finance approvals, IT automation). Maintain “golden paths”: Starter templates (agent patterns, tool usage patterns) Integration examples (auth, secrets, external APIs, eventing) Debugging and evaluation workflows Ensure labs are runnable across customer environments with minimal friction. 3. Certification & Skill Milestones Define skill milestones and certification criteria aligned to the engagement phases: Training Certified (Build-ready) Guided Build Certified (Co-build capable) Production Certified (Operate-ready) Build assessments: knowledge checks, hands-on practical tests, and rubric-based evaluations. Partner with Customer Success / Enablement leads to track certification progress and intervene when teams fall behind. 4. Guided Build Reinforcement (Coaching in Real Implementations) Reinforce training concepts during Guided Build by pairing with customer developers and teams. Help customers adopt best practices for: agent design and decomposition tool creation and integration reliability prompt / policy / safety guardrails testing, evaluation, and regression control release and rollout strategies Identify recurring customer pitfalls and convert them into improved training modules and reusable assets. 5. Production Enablement & Operational Readiness (Assisted Production) Collaborate with SRE/DevOps to create production enablement content: operational runbooks and SOPs monitoring and alerting checklists incident simulations, escalation playbooks Teach customers to run the Agentic AI Builder at enterprise scale: handling failures, timeouts, retries managing secrets, permissions, and audit logs performance and throughput considerations governance: review gates, standards, and approvals 6. Feedback Loop Into Product & DX Improvements Act as a “field signal amplifier” for the Agentic AI Builder: synthesize feedback from training, labs, and office hours highlight product gaps, UX friction, documentation needs propose improvements to reduce onboarding time and support tickets Partner with engineering to ensure enablement content stays current with releases. Required Skills & Qualifications 8–12+ years of experience as a software engineer, solutions engineer, product engineer, solution architect, or developer advocate—plus 3–5+ years in technical training, enablement, or mentoring roles. Strong experience building and operating enterprise SaaS products , APIs, and integrations. Proven ability to translate complex systems into clear learning paths and hands-on labs. Comfortable teaching both: builder-driven workflows (templates, config, guardrails), and engineering workflows (APIs, debugging, CI/CD, testing). Strong understanding of cloud systems (AWS/GCP/Azure), auth (OAuth/JWT), observability, and production operations. Excellent communication and facilitation skills with enterprise engineering audiences. Nice to Have Experience with agentic systems, orchestration frameworks, or AI automation products. Familiarity with LLM evaluation, regression testing, prompt/agent debugging methodologies. Prior experience enabling external enterprise customers at scale. What Success Looks Like (Outcomes & Metrics) Customer teams reach “Build-Ready” certification faster (reduced time-to-proficiency). Higher % of customer-led build tasks (reduced dependency during Guided Build). Higher “first-time-right” production readiness (fewer go-live escalations). Fewer repeat support questions due to better labs/docs/self-serve paths. Improved adoption and expansion due to confident internal champions. Why Join Ema Shape how enterprises adopt and scale agentic AI—directly influencing customer outcomes. Work at the intersection of AI product engineering, developer experience, and education . High ownership: build the enablement engine for a rapidly evolving product. Partner closely with world-class engineers, applied AI teams, and product leaders. Competitive compensation, meaningful ownership, and rapid career growth. Ema’s Culture & Values High Bar on Quality – We value excellent, production-grade thinking. Ownership & Accountability – You own results, not just training sessions. Impact-Driven Approach – Enablement success is measured by customer independence. Team Collaboration & Growth – We learn fast and teach each other. No Hierarchy, Just Execution – We move quickly, stay humble, and deliver.

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