AI Engineer

VueData Technologies Private Limited; Kirkland (WA); On-site; USD 80,000 - 110,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Job summary

VueData Technologies Private Limited is seeking a Senior AI Engineer to design and deploy agentic AI systems for production use. You will work with frontier LLMs, MCP tool integration, and RAG pipelines, building scalable AI applications on AWS Bedrock.

You will lead workflows involving reasoning, planning, routing, and human-in-the-loop patterns, ensuring robust observability, security, and cost-aware decisions while collaborating with product and engineering teams to move ideas from POC to

Qualifications

• 5+ years of software engineering experience, preferably backend/cloud/distributed apps.
• 2+ years hands-on with Generative AI, LLM apps, and agentic frameworks.
• Experience bringing AI/LLM applications from prototype to production.

Responsibilities

• Design, develop, and deploy agentic and multi-agent AI systems for production use cases.
• Create agent workflows including reasoning, planning, routing, delegation, tool execution, memory, state management, checkpointing, parallel execution, and human-in-the-loop patterns.
• Work with frontier LLMs and make practical decisions on model selection, prompting, structured outputs, context management, latency, token usage, quality, and cost.
• Build and integrate MCP servers, reusable tools, and function/tool-calling workflows connecting agents to APIs, databases, and internal apps.
• Orchestrate production-grade agent workflows and multi-agent systems.
• Develop AI applications using AWS Bedrock, including foundation models, Knowledge Bases/RAG, Guardrails, and related services.
• Build RAG and enterprise retrieval pipelines including ingestion, embeddings, vector search, reranking, metadata filtering, and grounding.
• Design multi-model architectures based on task complexity, quality, latency, and cost.
• Implement LLM observability and evaluation (tracing, tool execution monitoring, grounding, latency, token usage, task completion).
• Implement AI security patterns such as guardrails, prompt-injection defenses, tool permissioning, and credential management.
• Build reusable agent platforms and frameworks beyond chatbots.
• Use AI coding assistants and coding agents for development, debugging, testing, refactoring, and code analysis while owning code quality and architecture.
• Partner with product and engineering teams to move AI use cases from POC to production.

Skills

Python

Generative AI

LLMs

Agentic architectures

Multi-agent orchestration

AWS Bedrock

LangGraph

LangChain

LlamaIndex

CrewAI

AutoGen

GitHub Copilot

Tools

Lambda

ECS/EKS

API Gateway

S3

DynamoDB/RDS

OpenSearch

SQS/SNS

CloudWatch

Cursor

Claude Code

Codex

Job description

VueData is hiring a Senior AI Engineer to build production-ready agentic AI and LLM platform capabilities, with AWS Bedrock, RAG, guardrails, and MCP-based tool integration.

Responsibilities

• Design, develop, and deploy agentic and multi-agent AI systems for production use cases
• Create agent workflows that include reasoning, planning, routing, delegation, tool execution, memory, state management, checkpointing, parallel execution, and human-in-the-loop patterns
• Work with frontier LLMs and make practical decisions across model selection, prompting, structured outputs, context management, latency, token usage, quality, and cost
• Build and integrate MCP servers, reusable tools, and function/tool-calling workflows connecting agents to APIs, databases, enterprise systems, and internal applications
• Orchestrate production-grade agent workflows and multi-agent systems
• Develop AI applications using AWS Bedrock, including foundation models, Knowledge Bases/RAG, Guardrails, and related services
• Build RAG and enterprise retrieval pipelines covering ingestion, embeddings, vector search, reranking, metadata filtering, and grounding
• Design multi-model architectures based on task complexity, quality, latency, and cost
• Implement LLM observability and evaluation, including tracing, tool execution monitoring, response quality, grounding, hallucination signals, latency, token consumption, and task completion
• Implement AI security patterns such as guardrails, prompt-injection defenses, tool permissioning, credential management, and safe agent execution
• Build reusable agent platforms and frameworks (beyond standalone chatbots)
• Use AI coding assistants and coding agents for development, debugging, testing, refactoring, and code analysis while maintaining ownership of code quality and architecture
• Partner with product and engineering teams to move AI use cases from POC to production

Requirements

• Python skills with experience building production APIs and backend services
• Hands-on experience with Generative AI, LLMs, agentic architectures, and multi-agent orchestration
• Experience with frontier models such as OpenAI GPT, Anthropic Claude, Google Gemini, Meta Llama, or equivalent
• Hands-on experience with MCP, tool/function calling, structured outputs, and agent-to-tool integration
• Experience with AWS Bedrock and building AI/LLM applications on AWS
• Experience with one or more agentic AI frameworks: LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, or equivalent
• Strong understanding of RAG, embeddings, vector databases, semantic search, and reranking
• Experience with LLM observability, tracing, evaluation, and production monitoring using tools like Langsmith or equivalent
• Working knowledge of AWS services: Lambda, ECS/EKS, API Gateway, S3, DynamoDB/RDS, OpenSearch, SQS/SNS, CloudWatch
• Comfortable with AI-assisted development using tools such as GitHub Copilot, Cursor, Claude Code, Codex, or similar coding agents

What We Are Looking For

• Not a traditional data science or model-training role
• Comfort moving between an LLM, agent workflow, MCP tool, Python service, RAG pipeline, and AWS Bedrock, with understanding of how these pieces work together in a reliable production system
• AI-native approach to software development using AI coding tools extensively while retaining ownership of architecture, code quality, testing, security, and the final implementation

Technologies

• Python; Generative AI; LLMs; agentic architectures; multi-agent orchestration
• Frontier LLMs: OpenAI GPT; Anthropic Claude; Google Gemini; Meta Llama
• MCP; tool/function calling; structured outputs
• AWS Bedrock; Knowledge Bases/RAG; Guardrails; RAG; embeddings; vector search; reranking; metadata filtering; grounding
• LLM observability: Langsmith
• AWS: Lambda; ECS/EKS; API Gateway; S3; DynamoDB/RDS; OpenSearch; SQS/SNS; CloudWatch
• Agentic frameworks: LangGraph; LangChain; LlamaIndex; CrewAI; AutoGen
• AI coding assistants and coding agents: GitHub Copilot; Cursor; Claude Code; Codex

Location and Salary

• Location: Kirkland, WA (onsite)
• Salary: USD 80,000 - 110,000 per yearly

Experience

• 5+ years overall software engineering experience, preferably across backend, cloud, or distributed applications
• 2+ years hands-on experience with Generative AI, LLM applications, and agentic AI frameworks
• Experience taking AI/LLM applications from prototype through production

Benefits

• Health insurance
• Paid time off