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We are looking for an experienced Backend Engineer (4+ years) to join the team as an AI Integration Engineer, supporting one of our enterprise clients as part of their AI-Native Development program.

In this role, you will act as an AI Champion and Technical Mentor within the clients R&D organization. Your mission is to help development teams effectively integrate AI tools, agentic coding workflows, and best practices into their daily software development lifecycle (SDLC). You will help guide teams through AI adoption, help overcome resistance, and ensure AI delivers real value.

This is not a feature-delivery or coding-focused role, especially in the early stages, the position is centered on enablement, training, and integration, working closely with teams to embed AI development tools into real workflows and support the organizations AI transformation.

This is a high-impact role focused on technical enablement, AI expertise, and effective collaboration with development teams and intended for experienced engineers who actively use AI in their day-to-day development work and are looking to influence how teams work. Success in this role looks like teams shipping faster and smarter with AI, not lines of code written.



What Youll Do:

● Help drive adoption and optimization of GitHub Copilot and AI dev tools

● Support (mostly) backend engineers, answer technical questions and help unblock teams

● Continuously track the AI tooling landscape and best practices

● Measure impact, identify gaps and improvement opportunities across the SDLC

● Navigate and reduce change resistance to change with patience and empathy

● Partner with DevOps, architects, and management to track and optimize AI utilization

● Build and maintain a library of reusable AI assets (prompts, rules, agent workflows, playbooks) tailored to the clients stack

● Serve as the go-to escalation point for GitHub Copilot-related issues, edge cases, and feature rollouts

Were looking for an experienced Data Engineer to join our DEX Platform and help drive the next stage of our growth. In this role, youll design, build, and scale data infrastructure and advanced processing pipelines that power real-time insights and intelligent automation across our platform.
As a senior data engineer, youll own the full service lifecycle-from architecture and development to deployment, monitoring, and scaling-while ensuring data quality, reliability, and compliance. Youll work closely with backend, AI, and data teams to deliver robust, production-ready systems that support our AI-first strategy and our mission to make the workplace run itself.

We are looking for a Software Engineer (4+ years) with experience working with COBOL/Mainframe to join the team as an AI Integration Engineer, supporting one of our enterprise clients as part of their AI-Native Development initiative.

In this role, youll act as an AI Champion and Modernization Leader, working closely with development teams maintaining and evolving mainframe applications. Your mission is to help these teams integrate AI tools, agentic coding workflows, and emerging AI development best practices into their legacy and hybrid SDLC environments.

The focus is on enablement, training, and integration - not direct feature delivery. Youll bridge the gap between traditional mainframe development and AI-assisted software engineering, empowering teams to leverage tools like GitHub Copilot and emerging large-language-model (LLM) capabilities to accelerate modernization and improve developer experience.

This is a high-impact, high-visibility position designed for engineers who are hands-on with AI tools and want to influence how enterprise teams evolve their engineering practices. Success in this role looks like legacy teams delivering faster and smarter with AI - not lines of COBOL code written.

What Youll Do:

● Drive adoption and optimization of GitHub Copilot and other AI development tools in a variety of environments, including COBOL/Mainframe

● Mentor and support mainframe and backend engineers; answer questions, demonstrate workflows, and unblock teams

● Identify opportunities to use AI for code understanding, refactoring, documentation, and modernization

● Continuously track the evolving AI tooling landscape, surfacing relevant capabilities for mainframe use cases

● Measure impact, collect feedback, and identify improvement opportunities across the modernization lifecycle

● Navigate resistance to change with patience and empathy while promoting a learning culture

● Build a library of reusable AI assets (prompts, scripts, workflows) tailored to mainframe and integration contexts

● Partner with DevOps, architects, and management to track adoption and optimize AI utilization across projects

● Serve as the internal expert for GitHub Copilot and related AI dev tools, piloting new features, and best practices