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.