# GTM Engineer at Showpad

> India · Unspecified · Software engineering · open. Source: https://alderhq.app/jobs/greenhouse%3Ashowpad%3A8319730 (read 2026-11-09).

## Facts (observed)

- Company: [Showpad](https://alderhq.app/companies/showpad)
- Location text: Pune; Pune
- Where it can be done from (inferred): India (evidence: "Location lists "pune"")
- Posted: 2026-10-23 (17 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/showpad/jobs/8319730
- Skills listed (inferred): AWS, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (Pune, n 3): p25 ₹28.4L, median ₹32.3L, p75 ₹35.7L
- Licensed UK sponsor: registered as "Showpad Ltd" (checked 2026-11-09, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers))

## Description (the employer's text)

Summary: We are seeking a skilled GTM Engineer to join our dynamic team. This role plays a critical part in designing, building, and deploying AI agents and AI-enabled workflows, leveraging advanced technologies to drive business outcomes in a B2B SaaS environment. The ideal candidate will have a strong background in GTM processes, workflow automation, AWS, cloud engineering, and AI technologies.

### Responsibilities

- Develop and implement end-to-end GTM strategies and processes within a B2B SaaS environment.
- Create and optimize multi-system workflows and automations using REST APIs and event-driven integration patterns.
- Design and deploy serverless applications and event-driven architectures using AWS services.
- Build and integrate AI agents and workflows using Amazon, Claude/Anthropic models, and approved business systems.
- Collaborate with stakeholders to translate business problems into effective technology solutions.
- Ensure AI agents and workflows meet standards for accuracy, reliability, scalability, and security.
- Contribute to the development of standards for AI agent lifecycle management and observability.
### Required Skills

### GTM & Business Experience

- 6+ years of experience working directly with GTM processes and systems in a B2B SaaS or technology environment.
- Strong understanding of end-to-end Lead-to-Revenue and customer lifecycle processes.
- Demonstrated understanding of Sales, Marketing, Customer Success, and Revenue Operations workflows.
- Strong understanding of core SaaS commercial concepts and metrics.
- Experience translating business problems into process and technology solutions.
- Demonstrated ability to work directly with business stakeholders and challenge or refine requirements.
- Experience working across multiple GTM platforms and understanding cross-system dependencies.
### Workflow Automation & Integration

- Strong understanding of REST APIs, webhooks, JSON, OAuth, authentication, and event-driven integration patterns.
- Experience designing multi-system workflows and automations.
- Experience with workflow orchestration technologies.
- Ability to evaluate when low-code/no-code automation is appropriate versus custom development.
- Experience with platforms such as Zapier, n8n, Workato, Make, Tray.io, or comparable technologies is beneficial but not required.
- Experience with web scraping, browser automation, data extraction, or related technologies is beneficial.
- Ability to quickly learn and evaluate emerging automation and data acquisition technologies.
### AWS & Cloud Engineering

- Hands-on experience with AWS Lambda and serverless application patterns.
- Experience with AWS Step Functions or comparable workflow orchestration concepts.
- Experience with Amazon EventBridge and event-driven architecture.
- Experience with Amazon Bedrock or demonstrated experience building applications using foundation-model APIs.
- Familiarity with API Gateway, CloudWatch, IAM, Secrets Manager, S3, queues, databases, and related AWS services.
- Understanding of cloud security, permissions, monitoring, and production support practices.
### AI Agents & Agentic Orchestration

- Design, build, and deploy AI agents and AI-enabled workflows within the approved architecture.
- Use Amazon and Claude / Anthropic models for reasoning, classification, summarization, research, recommendations, and decision support.
- Build agentic workflows combining LLM reasoning with structured business data, APIs, deterministic rules, web-derived information, and approved tools.
- Integrate agents with approved business systems and data sources through available APIs, connectors, and Model Context Protocol (MCP) capabilities.
- Understand how to discover, configure, and use available MCP servers and tools within AI workflows.
- Evaluate when an existing MCP capability can simplify access to a system or data source rather than building a custom integration.
- Design prompts, context, structured outputs, tool/function calling, guardrails, and human-in-the-loop patterns.
- Determine when deterministic workflow logic should be used instead of an LLM or agent.

---
Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Ashowpad%3A8319730 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.