GTM Systems Engineer (AI Engineer)

GTMforge — GTM Engineer (AI Agents & AWS)Location: Pune, India, hybrid (2 days a week in the office)Shift: EMEA hours, starting 12:30 PM ISTExperience: 6+ yearsEmployment: Full-time, on GTMforge payroll, deployed as a dedicated engineer with a B2B SaaS clientAbout the roleYou’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-haveGTM 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 otherWorkflow 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 neededAWS 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 supportAI 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 managementAI 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 AIGood 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