Job Description: Corporate Trainer / Subject Matter Expert – Agentic Workflows & AI AutomationRole Overview
We are seeking an experienced Technical Corporate Trainer / Subject Matter Expert (SME) to design and deliver an intensive, hands-on, 1.5-day on-site corporate training program at our client's location in Bangalore. The training cohorts will consist of approximately 30 engineering professionals per batch, spanning a diverse range of experience levels from freshers to lateral hires.
The ideal candidate is an enterprise-grade engineer turned high-impact educator. You will move our client's engineering teams past basic, single-prompt AI code generation and equip them to orchestrate parallel multi-agent fleets. You will guide engineers through building isolated developer environments, setting up scoped subagents, securing infrastructure using Model Context Protocol (MCP), and deploying automated verification gates inside CI/CD pipelines to ensure all agent outputs are safe to merge at an enterprise production bar.
Key Responsibilities1. On-Site Corporate Delivery & Classroom Management
- Deliver Client-Site Training: Lead high-energy, high-density, keyboard-driven corporate training sessions on-site at the client's facility in Bangalore for batches of 30 engineers.
- Facilitate Mixed-Level Cohorts: Seamlessly manage a classroom containing both freshers and senior lateral engineers, adjusting delivery style, technical depth, and pacing to keep all participants engaged and learning.
- Live Lab Mentorship: Direct and circulate the floor during intense, real-world backlog sprints to unblock engineers on complex git worktree conflicts, context leaking, model stalling, and enterprise authentication issues.
- Interactive Code Clinics: Conduct live peer-critique and show-and-tell sessions, breaking down complex enterprise edge cases like context rot, flaky assertions, and prompt-injection vulnerabilities.
2. Curriculum Execution & Pipeline Architecture
- Parallel Workspace Execution: Train engineers to leverage advanced Git configurations (worktrees, port-offsets, and service isolation) to run multiple agents concurrently without resource collisions.
- Subagent Specialization: Guide the team in authoring domain-specific subagents (e.g., Reviewers, Test-Writers, Explorers) under strict, least-privilege tool permissions.
- Context Engineering: Establish robust repository guidelines by implementing path-scoped rules, progressive disclosure configurations, and custom slash-commands to optimize token windows and agent accuracy.
- Secure Tool Integration: Teach secure integration patterns for Model Context Protocol (MCP) servers, guiding teams through vulnerability scanning and prompt-injection guardrails.
- Automated Verification: Help teams design and deploy automated evaluation harnesses and CI review gates to catch regressions and shallow agent-written tests before human review.
Required Skills & Qualifications1. Corporate Training & Pedagogy Requirements
- Proven Corporate Training Experience: A solid track record of delivering technical training programs directly to corporate clients on-site.
- Client-Facing Professionalism: Excellent communication, presentation, and classroom management skills appropriate for a high-stakes enterprise client environment.
- Adaptability: Demonstrated ability to mentor and bridge knowledge gaps for a combined audience of freshers and experienced lateral hires simultaneously.
2. Technical Competencies
- Engineering Depth: Extensive professional experience in software engineering, with deep fluency in writing, refactoring, and debugging enterprise codebases.
- Advanced Git Fluency: Mastery of advanced version control mechanisms, including git worktree management, branch isolation strategies, and sequencing complex merge conflicts.
- Agentic Ecosystem Expertise: Practical experience orchestrating advanced AI development tools or developer systems (e.g., Cline, Aider, Roo Code, Cursor, Copilot Workspace). Proficient in multi-agent orchestration, prompt engineering, and tool calling.
- CI/CD & Testing Infrastructure: Hands-on experience building automated testing suites (unit, integration, E2E) and integrating automation/evaluation gates into standard CI environments (e.g., GitHub Actions, GitLab CI, Jenkins).
- Security Mindset: Practical understanding of LLM security parameters, including tracking and mitigating risks like prompt injection, tool poisoning, and insecure resource exposure.
Logistics & Engagement Details
- Location: On-site at the client's office in Bangalore, India.
- Batch Size: 30 professional engineers per batch.
- Format: 1.5 Days per batch (75% active keyboard/lab time).
