AI Engineer

Placement Type:

Temporary

Salary:

$47.82-53.13 Hourly

Start Date:

Nov 9, 2026

Duration:

6 months

Our client, a premier financial services institution, is dedicated to empowering individuals and institutions through innovative technology and robust financial solutions. Partnering with Aquent, they are at the forefront of leveraging artificial intelligence to redefine how they serve their customers and operate their business. This is an exceptional opportunity to join a team that values innovation, collaboration, and making a tangible impact on cutting-edge AI initiatives.

Are you a passionate technologist ready to make a significant impact? We are thrilled to partner with our client, a leader in financial innovation, to find a talented professional who will be instrumental in shaping the future of AI-powered applications and services. In this dynamic role, you will be at the heart of designing, developing, and deploying cutting-edge AI solutions that directly enhance customer experiences and drive operational excellence. You'll contribute to projects that improve developer and customer productivity, build scalable and secure AI services, and demonstrate ownership from initial design through to production support, all while collaborating effectively across diverse teams. This position offers the chance to independently deliver high-quality AI features, with the benefit of technical guidance from senior engineers and architects, fostering continuous growth and learning.

Key Responsibilities

• Design, develop, test, and deploy AI-enabled applications and services, ensuring high quality and reliability.
• Build and integrate Generative AI solutions utilizing large language models (LLMs).
• Develop sophisticated AI agents, workflows, prompts, tools, and orchestration frameworks.
• Implement advanced retrieval-augmented generation (RAG), semantic search, and knowledge retrieval solutions.
• Construct APIs, microservices, and robust backend services to support demanding AI workloads.
• Evaluate, benchmark, and optimize AI model performance, quality, cost, and latency.
• Develop automated testing, monitoring, and observability strategies for AI applications.
• Collaborate with product owners and business stakeholders to translate complex requirements into innovative technical solutions.
• Implement responsible AI practices, security, privacy, and governance controls within all AI solutions.
• Contribute significantly to architectural decisions, coding standards, and engineering best practices.
• Support AI applications in production, participating in troubleshooting and incident resolution to maintain operational excellence.

Must-Have Qualifications

We are looking for an individual with a solid foundation in software development and a proven track record in AI/ML applications. Your expertise will be critical in driving our innovative projects forward.

• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a closely related technical field.
• 3-6 years of professional software development experience.
• 2+ years of hands-on experience building AI/ML or Generative AI applications.
• Strong programming proficiency in one or more of the following languages: Python, Java, C#, or TypeScript/JavaScript.
• Demonstrated experience developing REST APIs and distributed services.
• Practical experience working with major cloud platforms such as Azure, AWS, or GCP.
• A strong understanding of core software engineering fundamentals, including design patterns, testing methodologies, CI/CD pipelines, security best practices, and observability.

Nice-to-Have Qualifications

These qualifications will set you apart and allow you to hit the ground running, contributing to even more complex and impactful projects from day one.

• Experience with leading LLM platforms such as OpenAI, Anthropic Claude, Azure OpenAI, or Gemini.
• Proficiency in building advanced AI agents, tool calling frameworks, and multi-agent workflows.
• Experience with RAG architectures and working with vector databases.
• Familiarity with prompt engineering techniques and evaluation frameworks.
• Experience with containerization and orchestration technologies like Docker, Kubernetes, or Cloud Run.
• Experience working within Agile development environments.