Integration Engineer II, AI & Engineering/Engineering as a Service AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements. Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation. Recruiting for this role ends on 10/30/26. Work You'll Do You are a hands-on Python and AI Developer who builds, tests, and ships reliable software as part of an agile engineering team. You contribute to the design and implementation of cloud-native applications and AI-augmented features, growing your technical depth across the stack. You will work alongside senior engineers to grow your technical skills while making meaningful contributions to our projects. Key Responsibilities

• Support AI and emerging technology initiatives across business and technology teams.
• Work hands-on with AI/ML, Generative AI, and agentic AI solutions.
• Help develop and prototype AI use cases that solve real business problems.
• Evaluate and apply foundation models, LLMs, and modern AI frameworks.
• Contribute to RAG, memory systems, tool use, and function-calling patterns.
• Support multi-agent workflows and autonomous AI capabilities.
• Assist with AI experimentation, proof-of-concepts, and solution testing.
• Partner with data, engineering, and business teams to move AI solutions toward production.
• Support MLOps, AI Ops, deployment, monitoring, and CI/CD practices.
• Communicate technical AI concepts clearly to both technical and non-technical audiences.
• Promote responsible AI practices, including ethics, governance and bias mitigation.
• Collaborate with product managers, designers, and fellow engineers to translate requirements into technical solutions.
• Identify, diagnose, and resolve bugs and performance issues in development and production environments.
• Assist in breaking down technical requirements into well-scoped tasks and estimates. A successful candidate would possess these skills:
• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills
• Meticulous attentio.

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