Senior AI Engineer (Full-Stack) (Remote)
Employment Type: Full-Time
Location: Remote
About the Role
We are looking for a Senior AI Engineer with strong full-stack capabilities to join our engineering team. You will work across multiple client-facing projects that sit at the intersection of AI, data, and web—starting with a live production AI agent platform.
You should be comfortable owning features end-to-end, from LLM pipeline design through to a polished frontend experience.
What You'll Do
AI Agent Engineering
Design and build AI agent pipelines, including multi-node LangGraph graphs.
Implement intent routing, multi-turn conversational context, session state management, and tool integrations.
Develop multi-step reasoning pipelines and graph-based agent workflows.
RAG & Knowledge Systems
Build and maintain Retrieval-Augmented Generation (RAG) systems.
Design vector search architectures, embedding pipelines, retrieval grounding, and chunking strategies.
Implement hallucination mitigation techniques and retrieval evaluation frameworks.
LLM Integration & Optimization
Integrate and optimize Large Language Models (LLMs) including OpenAI, Gemini, and Anthropic.
Develop structured output workflows using JSON schemas.
Create effective prompt engineering strategies, few-shot examples, and context window management solutions.
Build provider-neutral client architectures to support multiple LLM vendors.
Full-Stack Development
Design, develop, and deploy end-to-end product features.
Build scalable FastAPI backends and React/Next.js frontends.
Implement Server-Sent Events (SSE) streaming and REST API contracts.
Deliver production-ready UI features independently without requiring dedicated frontend support.
Observability & Quality
Own LLM observability including:Token usage logging
Cost tracking
Fallback detection
Performance monitoring
Regression test suites
Build evaluation pipelines and golden test suites to ensure AI quality and consistency.
Client & Product Collaboration
Collaborate directly with clients and stakeholders to understand business requirements.
Translate requirements into scalable, maintainable software solutions.
Keep technical documentation, specifications, and test coverage aligned with product changes.
Must-Have Skills
AI Agent Engineering
LangGraph or equivalent graph-based agent frameworks.
Multi-step reasoning pipelines.
Tool usage and orchestration.
State management and conversational workflows.
RAG & Vector Search
End-to-end RAG pipeline design and implementation.
Experience with vector databases such as:Pinecone
Qdrant
pgvector
Weaviate
Chunking strategies and retrieval optimization.
Retrieval evaluation methodologies.
LLM Integration
OpenAI, Gemini, and Anthropic SDKs.
Prompt engineering and prompt optimization.
Structured JSON outputs.
Context window management.
Multi-provider LLM integrations.
Python Backend Development
Python 3.12
FastAPI
Async Python
Pydantic
SQLite
PostgreSQL
Redis
Pytest
Full-Stack Development
React
Next.js
TypeScript
Modern frontend architecture
API integration and state management
ML Engineering Fundamentals
Evaluation pipelines
Golden datasets and test suites
Regression tracking
Model performance monitoring
Good to Have
GIS & Mapping
ArcGIS REST APIs
GeoJSON
MapLibre GL JS
Spatial queries
(Strong advantage for initial project assignments.)
Data Visualization
Recharts
D3.js
Equivalent charting libraries
Cloud & DevOps
Docker
Azure
AWS
CI/CD pipelines
OIDC Authentication
Product Thinking
Ability to understand and interpret Figma designs.
Evaluate trade-offs between engineering effort and business value.
Deliver solutions aligned with business objectives.
Technologies You'll Work With
LayerTechnology Stack
Agent FrameworksLangGraph, LangChain
LLM ProvidersGemini, OpenAI, Anthropic
BackendPython 3.12, FastAPI, SQLite, Redis
FrontendNext.js 15, React 19, TypeScript, Zustand
Data & VisualizationRecharts, GeoJSON, MapLibre GL JS
InfrastructureDocker, Azure Pipelines, Azure AD
What We're Looking For
Someone who can independently own a feature from requirements gathering to production deployment.
Strong full-stack engineering capabilities with no hand-holding required between backend and frontend development.
Strong engineering judgment and the ability to push back when shortcuts introduce hallucination risks, reliability issues, or technical debt.
Comfortable working in ambiguous environments with evolving client requirements.
Experience delivering software in real-world production environments.
Excellent communication skills with the ability to explain AI system behavior and limitations to non-technical stakeholders.
Strong documentation and testing discipline.
Nice to Have (Domain Experience)
Experience in any of the following industries is a significant advantage, though not required:
Energy
Oil & Gas
Infrastructure
Enterprise GIS
Location: Remote
About the Role
We are looking for a Senior AI Engineer with strong full-stack capabilities to join our engineering team. You will work across multiple client-facing projects that sit at the intersection of AI, data, and web—starting with a live production AI agent platform.
You should be comfortable owning features end-to-end, from LLM pipeline design through to a polished frontend experience.
What You'll Do
AI Agent Engineering
Design and build AI agent pipelines, including multi-node LangGraph graphs.
Implement intent routing, multi-turn conversational context, session state management, and tool integrations.
Develop multi-step reasoning pipelines and graph-based agent workflows.
RAG & Knowledge Systems
Build and maintain Retrieval-Augmented Generation (RAG) systems.
Design vector search architectures, embedding pipelines, retrieval grounding, and chunking strategies.
Implement hallucination mitigation techniques and retrieval evaluation frameworks.
LLM Integration & Optimization
Integrate and optimize Large Language Models (LLMs) including OpenAI, Gemini, and Anthropic.
Develop structured output workflows using JSON schemas.
Create effective prompt engineering strategies, few-shot examples, and context window management solutions.
Build provider-neutral client architectures to support multiple LLM vendors.
Full-Stack Development
Design, develop, and deploy end-to-end product features.
Build scalable FastAPI backends and React/Next.js frontends.
Implement Server-Sent Events (SSE) streaming and REST API contracts.
Deliver production-ready UI features independently without requiring dedicated frontend support.
Observability & Quality
Own LLM observability including:Token usage logging
Cost tracking
Fallback detection
Performance monitoring
Regression test suites
Build evaluation pipelines and golden test suites to ensure AI quality and consistency.
Client & Product Collaboration
Collaborate directly with clients and stakeholders to understand business requirements.
Translate requirements into scalable, maintainable software solutions.
Keep technical documentation, specifications, and test coverage aligned with product changes.
Must-Have Skills
AI Agent Engineering
LangGraph or equivalent graph-based agent frameworks.
Multi-step reasoning pipelines.
Tool usage and orchestration.
State management and conversational workflows.
RAG & Vector Search
End-to-end RAG pipeline design and implementation.
Experience with vector databases such as:Pinecone
Qdrant
pgvector
Weaviate
Chunking strategies and retrieval optimization.
Retrieval evaluation methodologies.
LLM Integration
OpenAI, Gemini, and Anthropic SDKs.
Prompt engineering and prompt optimization.
Structured JSON outputs.
Context window management.
Multi-provider LLM integrations.
Python Backend Development
Python 3.12
FastAPI
Async Python
Pydantic
SQLite
PostgreSQL
Redis
Pytest
Full-Stack Development
React
Next.js
TypeScript
Modern frontend architecture
API integration and state management
ML Engineering Fundamentals
Evaluation pipelines
Golden datasets and test suites
Regression tracking
Model performance monitoring
Good to Have
GIS & Mapping
ArcGIS REST APIs
GeoJSON
MapLibre GL JS
Spatial queries
(Strong advantage for initial project assignments.)
Data Visualization
Recharts
D3.js
Equivalent charting libraries
Cloud & DevOps
Docker
Azure
AWS
CI/CD pipelines
OIDC Authentication
Product Thinking
Ability to understand and interpret Figma designs.
Evaluate trade-offs between engineering effort and business value.
Deliver solutions aligned with business objectives.
Technologies You'll Work With
LayerTechnology Stack
Agent FrameworksLangGraph, LangChain
LLM ProvidersGemini, OpenAI, Anthropic
BackendPython 3.12, FastAPI, SQLite, Redis
FrontendNext.js 15, React 19, TypeScript, Zustand
Data & VisualizationRecharts, GeoJSON, MapLibre GL JS
InfrastructureDocker, Azure Pipelines, Azure AD
What We're Looking For
Someone who can independently own a feature from requirements gathering to production deployment.
Strong full-stack engineering capabilities with no hand-holding required between backend and frontend development.
Strong engineering judgment and the ability to push back when shortcuts introduce hallucination risks, reliability issues, or technical debt.
Comfortable working in ambiguous environments with evolving client requirements.
Experience delivering software in real-world production environments.
Excellent communication skills with the ability to explain AI system behavior and limitations to non-technical stakeholders.
Strong documentation and testing discipline.
Nice to Have (Domain Experience)
Experience in any of the following industries is a significant advantage, though not required:
Energy
Oil & Gas
Infrastructure
Enterprise GIS