GTM Systems Engineer (AI Engineer)

r3 Consultant
Pune City, Maharashtra, India

GTMforge — GTM Engineer (AI Agents & AWS)

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
  • Tool/function calling
  • Agentic workflows and AI orchestration
  • MCP concepts and MCP-enabled tools
  • Connecting AI workflows to business systems and data sources
  • RAG concepts
  • Human-in-the-loop patterns
  • Model and agent evaluation
  • AI observability
  • AI security, guardrails, data privacy and responsible AI

Good to have

  • Zapier, n8n, Workato, Make, Tray.io or similar platforms
  • Web scraping, browser automation or data extraction
  • 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

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This is based in Pune City, Maharashtra.

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