Sr. AI Engineer

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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