GTM Engineer

LeanScale, Inc.; Pune District; On-site; INR 900,000 - 1,800,000; Full time

Job summary

LeanScale, Inc. in Pune seeks a GTM Engineer to design, build, and deploy AI-enabled workflows and GTM agents in a B2B SaaS setting. You will leverage AWS to implement serverless architectures and cross-system integrations while aligning with Sales, Marketing, and Revenue Ops teams.

You will translate complex business problems into scalable technical solutions, ensure accuracy and security, and contribute to lifecycle management and observability of AI workflows across Rippled platforms.

Qualifications

• 6+ years of experience with GTM processes in a B2B SaaS or tech setting.
• Understanding of end-to-end Lead-to-Revenue and customer lifecycle workflows.
• Experience translating business problems into process and technology solutions.
• Ability to work with stakeholders and refine requirements across GTM platforms.
• Experience with cross-system dependencies and multi-system orchestration.

Responsibilities

• Develop and implement end-to-end GTM strategies for B2B SaaS.
• Create and optimize multi-system automations via REST APIs and event-driven patterns.
• Design and deploy serverless apps and event-driven AWS architectures.
• Build AI agents and workflows using Amazon, Claude/Anthropic models, and approved systems.
• Collaborate with stakeholders to translate business problems into technology solutions.
• Ensure AI agents/workflows meet standards for accuracy, reliability, scalability and security.
• Contribute to standards for agent observability and lifecycle management.

Skills

GTM processes

Lead-to-Revenue

SaaS metrics

Stakeholder alignment

Cross-system deps

REST APIs

Workflow automation

Orchestration

Low-code automation

Zapier

n8n

Make

Web scraping

AWS Lambda

Step Functions

EventBridge

Bedrock

IAM

S3

Cloud security

MCP capabilities

Anthropic models

Prompt engineering

Structured outputs

Tool calling

AI agents

Agentic workflows

Tools

AWS Lambda

AWS Step Functions

Amazon EventBridge

Bedrock

API Gateway

IAM

S3

CloudWatch

Job description

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.
• Test agents and workflows for accuracy, reliability, security, latency, scalability, cost, and measurable business value.
• Contribute to standards for agent permissions, observability, evaluation, and lifecycle management.

AI & LLM Technologies

• Claude / Anthropic and/or other leading foundation models
• Prompt and context engineering
• Structured outputs
• Tool / function calling
• Agentic workflows and AI orchestration
• Model Context Protocol (MCP) concepts and use of MCP-enabled tools
• Connecting AI workflows to approved systems and data sources
• Retrieval-Augmented Generation (RAG) concepts
• Human-in-the-loop patterns
• Model and agent evaluation
• AI observability
• AI security, guardrails, data privacy, and responsible AI
• Prior MCP experience is beneficial but not required. Candidates should be able to quickly learn and leverage MCP-enabled capabilities as part of AI and automation workflows.