Employment Type: Full-Time
Location: Remote
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.
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Design and build AI agent pipelines, including multi-node LangGraph graphs.
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Implement intent routing, multi-turn conversational context, session state management, and tool integrations.
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Develop multi-step reasoning pipelines and graph-based agent workflows.
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Build and maintain Retrieval-Augmented Generation (RAG) systems.
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Design vector search architectures, embedding pipelines, retrieval grounding, and chunking strategies.
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Implement hallucination mitigation techniques and retrieval evaluation frameworks.
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Integrate and optimize Large Language Models (LLMs) including OpenAI, Gemini, and Anthropic.
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Develop structured output workflows using JSON schemas.
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Create effective prompt engineering strategies, few-shot examples, and context window management solutions.
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Build provider-neutral client architectures to support multiple LLM vendors.
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Design, develop, and deploy end-to-end product features.
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Build scalable FastAPI backends and React/Next.js frontends.
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Implement Server-Sent Events (SSE) streaming and REST API contracts.
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Deliver production-ready UI features independently without requiring dedicated frontend support.
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Own LLM observability including:
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Token usage logging
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Cost tracking
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Fallback detection
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Performance monitoring
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Regression test suites
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Build evaluation pipelines and golden test suites to ensure AI quality and consistency.
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Collaborate directly with clients and stakeholders to understand business requirements.
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Translate requirements into scalable, maintainable software solutions.
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Keep technical documentation, specifications, and test coverage aligned with product changes.
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LangGraph or equivalent graph-based agent frameworks.
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Multi-step reasoning pipelines.
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Tool usage and orchestration.
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State management and conversational workflows.
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End-to-end RAG pipeline design and implementation.
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Experience with vector databases such as:
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Pinecone
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Qdrant
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pgvector
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Weaviate
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Chunking strategies and retrieval optimization.
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Retrieval evaluation methodologies.
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OpenAI, Gemini, and Anthropic SDKs.
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Prompt engineering and prompt optimization.
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Structured JSON outputs.
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Context window management.
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Multi-provider LLM integrations.
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Python 3.12
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FastAPI
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Async Python
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Pydantic
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SQLite
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PostgreSQL
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Redis
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Pytest
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React
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Next.js
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TypeScript
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Modern frontend architecture
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API integration and state management
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Evaluation pipelines
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Golden datasets and test suites
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Regression tracking
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Model performance monitoring
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ArcGIS REST APIs
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GeoJSON
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MapLibre GL JS
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Spatial queries
(Strong advantage for initial project assignments.)
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Recharts
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D3.js
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Equivalent charting libraries
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Docker
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Azure
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AWS
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CI/CD pipelines
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OIDC Authentication
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Ability to understand and interpret Figma designs.
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Evaluate trade-offs between engineering effort and business value.
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Deliver solutions aligned with business objectives.
Agent Frameworks
LangGraph, LangChain
LLM Providers
Gemini, OpenAI, Anthropic
Backend
Python 3.12, FastAPI, SQLite, Redis
Frontend
Next.js 15, React 19, TypeScript, Zustand
Data & Visualization
Recharts, GeoJSON, MapLibre GL JS
Infrastructure
Docker, Azure Pipelines, Azure AD
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Someone who can independently own a feature from requirements gathering to production deployment.
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Strong full-stack engineering capabilities with no hand-holding required between backend and frontend development.
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Strong engineering judgment and the ability to push back when shortcuts introduce hallucination risks, reliability issues, or technical debt.
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Comfortable working in ambiguous environments with evolving client requirements.
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Experience delivering software in real-world production environments.
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Excellent communication skills with the ability to explain AI system behavior and limitations to non-technical stakeholders.
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Strong documentation and testing discipline.
Experience in any of the following industries is a significant advantage, though not required:
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Energy
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Oil & Gas
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Infrastructure
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Enterprise GIS
