Qvest.Us26mo ago

Senior Engineer (Applied AI / ML)

United States·AustinRemoteFull-timesenior

Data ScienceOtherEngineer

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Quick Summary

Overview

Who We Are Qvest US is the global leader in technology and business consulting for the Media & Entertainment and Consumer Packaged Goods & Retail industries. We strategize, advise, design,

Technical Tools

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Who We Are

Qvest US is the global leader in technology and business consulting for the Media & Entertainment and Consumer Packaged Goods & Retail industries. We strategize, advise, design, develop and implement future-forward business & technology solutions. With expertise in digital media supply chain, data & analytics, IP & rights management, broadcast transformation, Salesforce and applied AI, our exceptionally talented teams partner with Fortune 1,000 companies to revolutionize markets and set new industry standards.

About the IDC

The IDC is our Innovation and Development Center. We build custom software using modern technologies to solve complex business problems for our clients. We believe the best products and services are realized by knowledgeable, tight-knit teams aligned to a shared purpose and understanding. We're honored to be recognized by Fortune magazine and Great Place to Work as a Best Workplace in Texas!

Who we're seeking

As a Senior Engineer, you enjoy solving problems and thrive in fast-paced, collaborative environments. You are looking for a role where you can work on varied projects, and influence technologies and solutions for both Qvest internal and client external projects. You thrive in environments where you're able to demonstrate technical competency while working individually, closely with team members, or directly with our clients.

Specifically working in our Applied AI / ML practice, you are a self driven engineer who loves to identify and experiment with new approaches, technologies, or tools which will impact our projects or industry. Examples could include emergent architectural approaches, new cloud provider offerings, or productivity enhancers (new tooling, Chat-GPT, Copilots, or similar).

You will provide leadership within software teams; as a mentor, team-lead, trusted client-facing technologist and/or as a hands-on contributor

You will impact all phases of our projects and all phases of the SDLC

You will leverage your existing depth of knowledge to maximize your impact

You will grow into new and/or adjacent technologies and domains to broaden your impact

Present solutions to clients as well as Qvest team members

Shape the kind of technologies that we are going to be using

4-6 years in software development, including working in teams

Experience with agile methodologies such as Scrum, Kanban or XP

Experience in ML / Applied AI tools and patterns including LLM, MLOps, RAG

Experience using different models (OpenAI, ChatGPT, Claude, Amazon Bedrock, LLaMA etc..) and understanding applicability to purpose / use case balancing cost vs. functionality

Experience developing copilots

Experience developing RAG applications

Experience with and around discussing enterprise deployments, knowing the landscape of enterprises, (their API’s, systems etc..) and the ability to communicate with client leadership in this area

Experience with Vector Database and Embeddings

Experience with Graph Databases

Definition, utilization and implementation of CI/CD pipelines

Familiarity with SOA, Microservices, or similar architectural patterns

Experience constructing systems by utilizing a separation of concerns (good OOP, FP design, etc)

Experience with enterprise application integration, including defining the integration architecture, integration data flows and interfaces, integration mechanisms (e.g., async vs. synchronous), middleware, etc.

Experience with typical AuthN/AuthZ methods and products

Experience managing data, including the selection of persistence product, design of database schema, constraints and transaction boundaries, read/write design trade-off decisions and how it relates to mutable vs. immutable data state

Experience balancing feature development vs. technical debt accumulation in order to deliver business needs while also maintaining quality over time