Job Description :

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 webstarting 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 :

1. Token usage logging

2. Cost tracking

3. Fallback detection

4. Performance monitoring

5. 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 :

1. Pinecone

2. Qdrant

3. pgvector

4. 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 :

1. Python 3.12

2. FastAPI

3. Async Python

4. Pydantic

5. SQLite

6. PostgreSQL

7. Redis

8. Pytest

Full-Stack Development :

1. React

2. Next.js

3. TypeScript

4. Modern frontend architecture

5. API integration and state management

ML Engineering Fundamentals :

1. Evaluation pipelines

2. Golden datasets and test suites

3. Regression tracking

4. Model performance monitoring

Good to Have :

GIS & Mapping :

1. ArcGIS REST APIs

2. GeoJSON

3. MapLibre GL JS

4. Spatial queries

(Strong advantage for initial project assignments.)

Data Visualization :

1. Recharts

2. D3.js

3. Equivalent charting libraries

Cloud & DevOps :

1. Docker

2. Azure

3. AWS

4. CI/CD pipelines

5. 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 :

Layer Technology Stack :

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

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 :

1. Energy

2. Oil & Gas

3. Infrastructure

4. Enterprise GIS

Employment Type : Full-Time

Location : Remote