GTM Systems Engineer (AI Engineer)

R3 Consultant; Pune District; Hybrid; INR 2,500,000 - 4,000,000; Full time

Job summary

GTMforge in Pune, India, hybrid (2 days in office) is seeking an experienced engineer to design, build and deploy AI agents and AI-enabled workflows that drive GTM outcomes for a B2B SaaS client. The role requires hands-on expertise with GTM processes, workflow automation, AWS and AI technologies, and the ability to work across Sales, Marketing, Customer Success and RevOps.

You will create end-to-end GTM strategies, develop multi-system automations via REST APIs and event-driven patterns, deploy

Qualifications

• 6+ years directly working with GTM processes in B2B SaaS or tech.
• Deep knowledge of lead-to-revenue and customer lifecycle processes.
• Experience across multiple GTM platforms and cross-functional workflows.

Responsibilities

• Build end-to-end GTM processes in a B2B SaaS setting.
• Create multi-system workflows and automations using REST APIs.
• Design and deploy serverless apps on AWS.
• Integrate AI agents and workflows with business systems.
• Collaborate with stakeholders to translate problems into tech solutions.
• Ensure accuracy, reliability, scalability and security of agents/workflows.
• Define AI agent lifecycle standards and observability.

Skills

GTM processes

Workflow automation

AWS

AI technologies

GTM platforms

Tools

AWS Lambda

Step Functions

EventBridge

Bedrock

API Gateway

CloudWatch

S3

IAM

Job description

Location: Pune, India, hybrid (2 days a week in the office)

Shift: EMEA hours, starting 12:30 PM IST

Experience: 6+ years

Employment: Full-time, on GTMforge payroll, deployed as a dedicated engineer with a B2B SaaS client

About the role

You’ll design, build and deploy AI agents and AI-enabled workflows that drive go-to-market outcomes in a B2B SaaS environment. We need someone with a strong background in GTM processes, workflow automation, AWS and cloud engineering, and AI technologies.

What you’ll do

• Build and implement end-to-end GTM processes and strategies in a B2B SaaS setting.
• Create and optimise multi-system workflows and automations using REST APIs and event-driven integration patterns.
• Design and deploy serverless applications and event-driven architectures on AWS.
• Build and integrate AI agents and workflows using Amazon and Claude/Anthropic models, connected to approved business systems.
• Work with stakeholders to turn business problems into practical technology solutions.
• Make sure agents and workflows meet standards for accuracy, reliability, scalability and security.
• Help define standards for AI agent lifecycle management and observability.

Must-have

GTM and business

• 6+ years working directly with GTM processes and systems in B2B SaaS or tech
• Strong grasp of end-to-end lead-to-revenue and customer lifecycle processes
• Solid understanding of Sales, Marketing, Customer Success and RevOps workflows
• Strong command of core SaaS commercial concepts and metrics
• Track record of turning business problems into process and technology solutions
• Comfortable working directly with business stakeholders, including challenging and refining their requirements
• Experience across multiple GTM platforms, with an understanding of how they depend on each other

Workflow automation and integration

• Strong understanding of REST APIs, webhooks, JSON, OAuth, authentication and event-driven integration
• Experience designing multi-system workflows and automations
• Experience with workflow orchestration technologies
• Good judgement on when low-code/no-code fits and when custom development is needed

AWS and cloud

• Hands-on with AWS Lambda and serverless patterns
• Experience with AWS Step Functions or similar orchestration
• Experience with Amazon EventBridge and event-driven architecture
• Experience with Amazon Bedrock, or with building applications on 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

AI agents and orchestration

• Design, build and deploy AI agents and AI-enabled workflows within the approved architecture
• Use Amazon and Claude/Anthropic models for reasoning, classification, summarisation, research, recommendations and decision support
• Build agentic workflows that combine LLM reasoning with structured business data, APIs, deterministic rules, web-derived information and approved tools
• Connect agents to business systems and data sources through APIs, connectors and Model

Context Protocol (MCP) capabilities

• Discover, configure and use available MCP servers and tools, and judge when an existing MCP capability beats a custom integration
• Design prompts, context, structured outputs, tool/function calling, guardrails and human-in-the-loop patterns
• Know when deterministic 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 and LLM technologies (hands-on experience or strong practical knowledge)

• Claude/Anthropic and/or other leading foundation models
• Prompt and context engineering
• Structured outputs
• Agentic workflows and AI orchestration
• MCP concepts and MCP-enabled tools
• Connecting AI workflows to business systems and data sources
• Model and agent evaluation
• AI security, guardrails, data privacy and responsible AI

Good to have

• Zapier, n8n, Workato, Make, Tray.io or similar platforms
• Prior MCP experience (not required, but you should be able to pick it up quickly)
• Ability to quickly learn and evaluate new automation and data-acquisition technologies