ClickUp06/29/2026
Старший инженер-программист внутренних продуктов
Salary not specified
MARKET
15,667 ₽median for this role
Data Engineer · 11 jobs with disclosed pay
10,833half of the offers: 14,166–16,81220,833
The employer didn't disclose pay — compare with the market yourself.
Полная занятостьУдалёнка
Responsibilities
- 01Design, build, and operate Model Context Protocol servers that expose CRM, ticketing, analytics, and communication data to AI agents across the GTM stack
- 02Implement Okta PKCE authentication flows and RBAC policy enforcement so agents access only the data they're authorized to touch
- 03Maintain deployment infrastructure on AWS (Bedrock, Lambda, ECS, API Gateway) and contribute to GCP workloads where applicable
- 04Own observability: structured logging, distributed tracing, latency SLOs, and on-call runbooks for every production server
- 05Build and maintain multi-step autonomous agents that execute end-to-end GTM workflows — lead qualification, deal room assembly, onboarding automation, support triage, and more
- 06Architect prompt engineering frameworks, tool-call schemas, and agent evaluation harnesses that make AI behavior predictable and auditable
- 07Integrate with LLM providers (Anthropic, OpenAI, AWS Bedrock AgentCore) and maintain version-pinned, cost-tracked model configurations
- 08Deliver AI-powered internal applications (web apps, CLI tools, Slack integrations) that non-technical GTM stakeholders use without friction
- 09Own full-stack feature delivery across TypeScript/Node.js backends and React/TypeScript frontends for internal tooling
- 10Write Python automation scripts, ETL pipelines, and data transformation layers that feed GTM analytics and AI context
- 11Collaborate with Systems Engineering and GTM Engineering teams on cross-cutting API standards, data contracts, and integration patterns
- 12Conduct code reviews, establish engineering standards, and actively mentor junior engineers toward higher leverage
- 13Use AI coding assistants (Claude, Cursor, GitHub Copilot) as primary engineering accelerators — not supplements — to ship at a pace that punches above a single engineer's weight
- 14Document AI usage patterns, prompt templates, and agentic workflows so the team's collective throughput compounds
- 15Stay current on MCP protocol evolution, agent frameworks (LangGraph, CrewAI, custom), and emerging LLM capabilities; bring back what matters
Requirements
- 015+ years of professional software engineering experience with production systems
- 02Expert-level TypeScript and Node.js — idiomatic, typed, testable server-side code
- 03Strong Python — automation scripts, data pipelines, and scripting for AI/ML tooling
- 04Meaningful AWS deployment experience: Lambda, Bedrock, ECS/Fargate, API Gateway, IAM, Secrets Manager, CloudWatch
- 05Demonstrated experience integrating with LLM APIs (OpenAI, Anthropic, AWS Bedrock, or equivalent) and shipping AI-powered features to real users
- 06Solid foundation in REST API design, OAuth 2.0 / OIDC authentication, and secure credential management
- 07Experience with CI/CD pipelines, infrastructure-as-code (Terraform, CDK, or SAM), and cloud cost awareness
- 08Clear written communication: design docs, ADRs, and runbooks that others actually read
- 09Track record of using AI tools (LLM assistants, copilots, agentic workflows) as a genuine productivity multiplier — not a gimmick