This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer, Internally Deployed Products based in United States.
This role sits at the intersection of AI infrastructure and internal product engineering, focused on building and scaling production-grade systems that power go-to-market operations. You will design and operate backend platforms that expose enterprise data to AI agents securely and reliably. The environment is highly AI-native, with engineers expected to leverage LLM tools as core development partners. You will contribute to agent orchestration systems that automate complex business workflows across sales, marketing, and revenue operations. The role requires strong ownership across the full software lifecycle, from design to deployment and observability. You will also build internal tools used daily by hundreds of employees, ensuring high performance, security, and scalability. This is a fast-paced engineering culture where velocity, autonomy, and practical AI usage are central to success.
Accountabilities
- Design, build, and operate MCP server infrastructure enabling secure access to CRM, analytics, ticketing, and communication systems for AI agents
- Implement authentication and authorization mechanisms including OAuth, OIDC, Okta PKCE flows, and RBAC policies for secure data access
- Develop and maintain multi-step autonomous AI agents that execute GTM workflows such as lead qualification, onboarding, and support automation
- Build backend and frontend internal tools using TypeScript, Node.js, React, and Python for automation and data processing
- Define and maintain LLM integrations, prompt frameworks, tool schemas, and agent evaluation systems for reliable AI behavior
- Own production readiness including observability, logging, distributed tracing, SLOs, on-call support, and infrastructure reliability
- Collaborate with engineering teams on API standards, data contracts, CI/CD pipelines, and system architecture decisions
- Mentor engineers and contribute to engineering best practices, documentation, and code quality standards
Requirements
- 5+ years of software engineering experience building production-grade systems
- Expert-level proficiency in TypeScript and Node.js for backend development
- Strong Python skills for automation, scripting, and data pipelines
- Hands-on experience with AWS services such as Lambda, ECS/Fargate, API Gateway, IAM, and Bedrock
- Experience integrating with LLM APIs such as OpenAI or Anthropic and building AI-powered features
- Strong understanding of REST APIs, OAuth 2.0, OIDC, and secure authentication systems
- Experience with CI/CD pipelines, infrastructure-as-code tools, and cloud cost optimization practices
- Ability to write clear technical documentation including design docs and operational runbooks
- Demonstrated use of AI tools such as coding assistants or agentic workflows to improve productivity
- Strong communication skills and ability to collaborate across technical and non-technical teams
- Preferred: experience with MCP, CRM systems (Salesforce, HubSpot), GCP, React/Next.js, or agent frameworks like LangGraph or CrewAI
Benefits
- Competitive salary range: $160K – $210K
- Equity opportunities
- 401(k) retirement plan
- Health, dental, and vision insurance
- Flexible spending accounts
- Life and disability coverage
- Paid parental leave
- Flexible paid time off policy
- Employee wellness stipend
- Professional development stipend
- Enhanced employee assistance program
- Remote-first flexibility within the United States