About Centric Software:

Centric Software® is a global leader, providing an innovative and AI-enabled product-concept-to-commercialization platform for retailers, brands and manufacturers of all sizes. We equip retail, fashion, luxury, footwear, outdoor, home and consumer goods brands with pioneering best-of-breed solutions to plan, design, develop, source, comply, buy, make, price, allocate, sell and replenish products. Our technology powers brands to streamline processes, drive efficiency and operate with confidence in an ever-changing market.

Our story is one of rapid growth, bold ideas and extraordinary opportunities. We’re here to challenge the status quo—and we’re looking for brilliant people who want to do the same. No matter where you are in the world, this is your chance to be part of something exceptional.

Senior AI Engineer - AWS SaaS | Production RAG | AI Agents | AI-Augmented Engineering

Location: US, Canada or India

Compensation: $180,000 - $210,000 USD (based on location)

Job Summary

We are seeking a Senior AI Engineer to design, build, and operate production-grade AI systems within our enterprise, multi-tenant SaaS platform.

This is a hands-on engineering role for a senior SaaS architect who has evolved into an applied AI systems builder. You will architect and ship reliable, scalable AI capabilities used by enterprise customers in production environments.

This is not a research role.
This is not a prototype-only position.
This is a production AI systems engineering role embedded in a mature SaaS platform.

Requirements

Architect & Deliver Production AI Systems

Design and deploy Retrieval-Augmented Generation (RAG) systems integrated with enterprise data
Build hybrid search pipelines combining lexical (BM25) and semantic retrieval
Implement cross-encoder reranking to improve relevance and precision
Develop structured AI agents with controlled, deterministic tool execution
Continuously improve retrieval quality, task success rates, and system reliability

Build AWS-Native AI Services

Develop AI services using AWS Lambda
Orchestrate AI workflows using AWS Step Functions
Design deterministic state machines with robust retry, timeout, and idempotency strategies
Ensure systems are scalable, cost-efficient, observable, and production-ready

Own AI Quality & Reliability

Design and maintain evaluation pipelines for AI systems
Establish golden datasets and measurable quality benchmarks
Monitor retrieval performance, latency, cost, and system health
Improve AI reliability through disciplined iteration and measurement

Deliver Full-Stack AI Features

Build backend AI services in Python
Deliver AI-powered user experiences in React + TypeScript
Integrate AI workflows into enterprise-grade SaaS applications

Elevate Engineering Standards

Contribute reusable AI platform components
Mentor engineers in applied AI system design
Promote disciplined, measurable AI engineering practices

Requirements:

Core SaaS Engineering

10+ years of professional software engineering experience
Proven experience building and operating AWS-based SaaS platforms
Strong background in:
- Serverless architectures
- Microservices
- Multi-tenant enterprise systems
Backend expertise in Python
Full-stack capability with React + TypeScript
Deep experience with PostgreSQL, including:
- Performance tuning
- Indexing strategies
- Full-text search

Applied AI Engineering (Production Systems)

2–4+ years building production AI systems
Hands-on experience delivering multiple production RAG systems
Experience implementing hybrid search systems combining:
- BM25 (or equivalent lexical ranking)
- Semantic retrieval using embeddings
- Reranking techniques
Experience building AI agents with structured tool invocation
Experience designing evaluation frameworks and measurable AI quality systems

Strong understanding of:

Hallucination mitigation strategies
Prompt injection defense
Safe tool execution
Deterministic workflow design

Technical Expertise

We expect hands-on production experience with many of the following (or strong equivalents):

RAG & Retrieval Frameworks

LlamaIndex, LangChain, or similar frameworks

Search & Retrieval Infrastructure

PostgreSQL + pgvector (or equivalent vector database)
BM25 or similar lexical ranking
Hybrid retrieval architecture

Agent Frameworks

Structured tool-calling frameworks (e.g., Google ADK, AWS Strands, or similar)

Orchestration (Required)

AWS Step Functions
AWS Lambda
Deterministic state machine design

Evaluation & Observability

RAG evaluation frameworks (e.g., RAGAS, DeepEval, or similar)
LLM-as-judge evaluation approaches
AI system monitoring and observability (e.g., OpenTelemetry)
Monitoring for latency, cost, and quality drift

AI-Augmented Software Development (Core Competency)

This role requires demonstrated professional use of AI-assisted engineering tools.

You should have hands-on experience using tools such as:

OpenAI Codex or Codex-based environments
Claude Code
GitHub Copilot-class systems
Equivalent AI-powered development platforms

You should be able to demonstrate how you:

Use AI code generation to accelerate backend and frontend development
Generate tests and refactor production code using AI tools
Scaffold services with AI assistance
Review and productionize AI-generated code responsibly
Integrate AI-assisted workflows into CI/CD pipelines
Maintain high engineering standards while leveraging AI acceleration

AI-augmented engineering is a required capability for this role.

What Strong Candidates Can Clearly Explain

A production RAG system they built end-to-end
How they improved hybrid retrieval relevance
An AI agent workflow and how tool execution was controlled
Their approach to measuring AI system quality
How they used AWS Step Functions to orchestrate AI workflows
How they leverage AI tools to improve engineering productivity without sacrificing quality

What This Role Is Not

Not a pure machine learning research role
Not a fine-tuning-only role
Not a prompt engineering-only role
Not a chatbot demo builder role

The Ideal Candidate

You are a senior SaaS engineer who:

Designs systems for reliability and scale
Ships production AI capabilities
Measures quality, not just functionality
Understands cost and performance tradeoffs
Uses AI to build better software—faster—without lowering standards

Centric Software provides equal employment opportunities to all qualified applicants without regard to race, sex, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status or genetic information.

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