Senior AI Applications Developer, Agents, LLMs

Jobtailor; Barueri; Presencial; BRL 180 000 - 350 000; Tempo integral

Resumo da oferta

Jobtailor is seeking a senior engineer to design and deploy production-grade LLM-powered applications and tooling, with a strong emphasis on API-led integration, automation, and cost-aware performance optimization. You will own end-to-end systems, integrate with MCP-based tools, and ensure robust observability and security across platforms.

The role requires hands-on work across Python, Node/TypeScript, and .NET/C#, plus experience with LLM APIs, orchestration frameworks, and enterprise

Qualificações

• 6+ years of software development experience with production ownership.
• Proficiency in at least two stacks: Python, .NET/C#, and Node/TypeScript.
• Hands-on experience building with LLM APIs, including function/tool calling and streaming.
• Familiarity with MCP or equivalent tech and how an agent interacts with external tools.
• Experience with automation/integration platforms: MuleSoft, n8n, Logic Apps, Make, Power Automate, or Workato.
• Understanding of API-led integration, versioning, gateways, and contracts between systems.
• At least one LLM application deployed to production with cost, latency, and behavior management.
• Strong fundamentals in REST APIs, messaging/queues, relational databases, Docker, CI/CD, and Git.
• Knowledge of vector databases (pgvector, Qdrant, Weaviate, Pinecone) and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel).
• Experience publishing or maintaining an MCP server or building custom nodes/integrations in n8n.

Responsabilidades

• Design and build production applications powered by LLMs, including assistants, tool-using agents, and automation features.
• Implement and evolve RAG pipelines, ingestion, chunking, embeddings, and hybrid search.
• Build evaluation layer with test datasets, quality metrics, and prompt regression testing.
• Monitor and optimize latency, cost per request, error rates, and hallucination rates.
• Optimize systems through caching, model routing, and context tuning.
• Integrate AI layer with existing .NET and Node/TypeScript systems while respecting contracts and security.
• Build and maintain MCP servers/clients to expose internal systems as tools for agents.
• Define permission scopes, tool contracts, and error handling.
• Orchestrate automations and integrations using n8n and iPaaS platforms like MuleSoft, Logic Apps, Make, and Workato.
• Determine what stays in low-code, becomes an API, or is coded.
• Expose and consume enterprise APIs within AI architecture, reusing business rules without duplication.
• Implement guardrails, sensitive-data handling, and observability (tracing, prompt logging, auditing).
• Conduct code reviews, write documentation, and raise technical standards.

Conhecimentos

Cross-stack collaboration

Production ownership

Observability

Prompt regression testing

Team collaboration

Ferramentas

Python

Node/TypeScript

.NET/C#

LLM APIs

REST APIs

Docker

CI/CD

Relational Databases

Vector Databases

MuleSoft

n8n

Azure Logic Apps

Make

Workato

LangChain

Descrição da oferta de emprego

• Design and build production applications powered by LLMs, including assistants, tool-using agents, workflow automations, and AI features embedded in existing products
• Implement and evolve RAG pipelines, ingestion, chunking, embeddings, hybrid search, and reranking
• Build the evaluation layer with test datasets, quality metrics, and prompt regression testing
• Monitor and optimize latency, cost per request, error rates, and hallucination rates
• Optimize systems through caching, model routing, and context tuning
• Integrate the AI layer with existing .NET and Node/TypeScript systems while adhering to contracts and security requirements
• Build and maintain MCP servers and clients to expose internal systems as tools for agents
• Define permission scopes, tool contracts, and error handling
• Orchestrate automations and integration workflows using n8n and iPaaS platforms such as MuleSoft/Anypoint, Azure Logic Apps, Make, and Workato
• Determine what should remain in low-code, become a managed API, or be implemented in code
• Expose and consume enterprise APIs within the AI architecture, transforming existing MuleSoft integrations into agent tools without duplicating business rules
• Implement guardrails, sensitive-data handling, and observability, including tracing, prompt logging, and auditing
• Conduct code reviews, write documentation, and raise the team’s technical standards

Requirements

• 6+ years of software development experience, with a track record of owning systems in production
• Proficiency in at least two of the team’s stacks: Python, .NET/C#, and Node/TypeScript—and a genuine willingness to work across them
• Hands-on experience building with LLM APIs (OpenAI, Anthropic, Gemini, Bedrock, or equivalent), including function/tool calling and streaming
• Familiarity with MCP or an equivalent technology, understanding how an agent discovers, calls, and receives results from an external tool, as well as what can go wrong along the way
• Experience with automation and integration platforms: MuleSoft (Anypoint Platform), n8n, Logic Apps, Make, Power Automate, or Workato
• Understanding of API-led integration, including API versioning, gateways, security policies, and contracts between systems
• At least one LLM application deployed to production, with experience managing cost, latency, and unexpected behavior
• Strong fundamentals in REST APIs, messaging/queues, relational databases, Docker, CI/CD, and Git
• Knowledge of vector databases such as pgvector, Qdrant, Weaviate, or Pinecone
• Knowledge of orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or LangGraph
• Experience publishing or maintaining an MCP server, or building custom nodes/integrations in n8n
• Knowledge of DataWeave, custom connectors, or Anypoint Platform administration
• Knowledge of event-driven architecture, including webhooks, queues, retries, and idempotency
• Knowledge of LLM evaluation and observability tools such as LangSmith, Langfuse, Braintrust, or Phoenix
• Knowledge of cloud platforms (Azure, AWS, or GCP) and infrastructure as code
• Knowledge of fine-tuning, quantization, or deployment of open-source models
• Open-source contributions or publicly available technical content

Core Competencies

Demonstrates expertise in designing and building production applications powered by LLMs, with a strong focus on API-led integration, automation, and optimization of systems. Proficient in managing cost, latency, and performance metrics while ensuring adherence to security and contract requirements.

Highest-signal resume keywords

• LLM Application Development
• API-Led Integration
• Automation and Integration Platforms
• Production System Ownership
• Cloud Platforms Knowledge

ATS Optimization Keywords

Hard Skills

• Python
• Node/TypeScript
• .NET/C#
• LLM APIs
• REST APIs
• Docker
• CI/CD
• Relational Databases
• Vector Databases
• Event-Driven Architecture

Industry Keywords

• MCP
• Hybrid Search
• Observability
• Prompt Regression Testing
• Cost Management

Tools & Technologies

• MuleSoft
• N8n
• Azure Logic Apps
• Make
• Workato