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Dmitriy B.
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Dmitriy B.

Multi-Agent AI Engineer | LangGraph & Agent Orchestration | AI Agent

🟢🟢 Available to start today 💎💎 Partner Verified AI Multi-Agent Developer ✅ I build AI agents and multi-agent systems that connect your tools and data. Each workflow moves a request toward a result your team can check. WHAT CAN MULTI-AGENT SYSTEMS DO FOR YOU? An AI agent can qualify leads, search documents, update your CRM, or schedule meetings. When a task needs several specialists, a multi-agent system gives each one a role and passes context between them. AI Agent Development starts with your process: what triggers the work, which tools agents can use, where a person needs to approve an action, and what a successful result looks like. HAVE I BUILT AI AGENTS AND MULTI-AGENT SYSTEMS LIKE YOURS? ✔ CONEXIAI — MULTI-AGENT RISK INTELLIGENCE I was the main developer of a Python and LangGraph system for business risk analysis. A supervisor routes reputation, competitor, market, and internal data research to specialist AI agents, then brings their findings into a risk report. This is my direct example of multi-agent orchestration. ✔ TELEGRAM ASSISTANT Built a LangChain AI agent in Telegram for lead intake, HubSpot and Supabase updates, scheduling, and email. Tool calling and memory let it turn a message into connected business actions. ✔ NOVARENT — REAL ESTATE AI Developed a Claude agent for NYC apartment searches and lead qualification. MCP tools handle listings, preferences, HubSpot updates, Gmail notifications, and calendar actions. ✔ E-COMMERCE SUPPORT Built an n8n AI agent with OpenAI, WooCommerce, Qdrant RAG, and Cohere Reranker. It retrieves product knowledge, checks live orders and deliveries, and routes complaints to human review. HOW WILL YOUR AI AGENTS WORK TOGETHER? I map the trigger, agent roles, tools, and expected output. For multi-agent work, I define who acts next, what context is passed, and when an agent should stop or ask for human approval. I scope agent workflows around: ✔ Tool calling with structured inputs and outputs. ✔ Retrieval and memory where the task needs them. ✔ Human approval before sensitive actions. ✔ Clear roles, routing, and handoffs between agents. Each step can be checked against your requirements. HOW WILL YOUR AGENT SYSTEM CONNECT TO YOUR TOOLS? API integration connects AI agents with the systems your team already uses. My project work includes HubSpot, Telegram, WhatsApp, Gmail, Google Calendar, WooCommerce, Supabase, and Google Sheets. I use n8n for workflow automation and MCP for controlled backend access. In a document RAG project, I filtered retrieval by user role before excerpts reached the model. WHAT MAKES AN AGENT SYSTEM PRODUCTION READY? A working demo is only the start. Production AI automation needs defined behavior when an API fails, data is missing, or a tool returns something unexpected. The scope can include: ✔ Error handling, retries, and recovery. ✔ Validation of agent outputs and tool inputs. ✔ Tests using real examples and acceptance criteria. ✔ Logs that show what happened and where work stopped. ✔ Permissions and human approval for sensitive actions. We agree on these checks before implementation, based on the tools involved and the cost of an error. WHICH TECHNOLOGIES SUPPORT YOUR AGENT WORKFLOWS? ✔ Python and LangGraph coordinate specialist agents and shared state in CONEXIAI. ✔ LangChain supports tool calling and memory in the Telegram assistant. ✔ n8n connects AI agents to business workflows, APIs, and human review. ✔ OpenAI and Claude models handle language tasks; Qdrant and Pinecone support RAG retrieval. ✔ React and Supabase support the applications and data behind these workflows. I choose tools for the work they do and how your team will maintain them. WHAT WILL YOU RECEIVE? We agree on scope, API integrations, and acceptance criteria. Delivery can move from a working prototype to connected agent workflows, testing, documentation, and a walkthrough with your team. WHAT WOULD YOU LIKE TO AUTOMATE FIRST? Send me your current process, tools, and desired result. I can suggest where one AI agent is enough and where several agents need to work together.

🇰🇿Almaty, Kazakhstan$25/hr100% JSS4.98 (43)Since Nov 2024
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Earnings and projects

MRR
$1.2k

Last 6 months ÷ 6

World#40,257 / 412k
🇰🇿Country#74 / 762
Revenue, last 30 days
$977

Last 6 months: $7.3k

World#43,540 / 412k
🇰🇿Country#78 / 762
Total earnings
$59k

Billed in all: $62k

World#66,462 / 412k
🇰🇿Country#163 / 762
Per project
$805

$455 in the last 6 months

World#141,081 / 412k
🇰🇿Country#295 / 762
Projects, last 6 months
16

Across 18 contracts

39% fixed61% hourly
World#8,872 / 412k
🇰🇿Country#13 / 762
Projects in all
73

Across 83 contracts

33% fixed67% hourly
World#40,823 / 412k
🇰🇿Country#77 / 762

Earnings, last 30 days

$62.2k+$977 earned in the last 30 daysBilled in all, before Upwork's fee · drag across the chart to see what was earned in any stretch
$61.0k$61.5k$62.0k$62.5kOct 8Oct 23Nov 7

Skill rankings: Top 12% in Python

Ranked by MRR among everyone on Upwork with the skill.

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