Senior Consultant (Applied AI Engineer)

Apex Systems•Glen Allen, VA

49d

About The Position

Apex is seeking a dynamic Senior Consultant with strong consultative skills to serve as an Applied AI Engineer. The role is hands-on and focused on building production-level solutions integrating AI technologies. As an Applied AI Engineer, you will focus on building solutions for internal and external customers, accelerating the adoption of AI while establishing and sharing best practices.

Requirements

Bachelor's degree in computer science, software engineering, data science or related technical field or comparable work experience, with significant experience on delivering AI-enabled applications
3+ years of practical technical experience with extensive background in AI-integrated application development
3+ years of experience with Python SDKs
1+ years of experience with building and deploying solutions in Microsoft Copilot Studio as well as Azure OpenAI
Strong knowledge of practical deployment of LLM/SLMs and tuning to reach and maintain production-grade quality thresholds
Experience in orchestrating GenAI applications using frameworks such as LangChain, semantic kernal, or Assistants API
Experience building RAG applications, including cloud search services such as Azure AI Search and CosmosDB, moving beyond limitations of vector databases and OSS solutions for quality and enterprise scale
Experience delivering these solutions in a cloud environment and experience working with cloud platforms (Azure a must, AWS and GCP nice to have)
Experience in a team-based environment
Willingness to perform limited periodic travel (for PI planning sessions, etc.)
Outstanding written and verbal communication skills and a desire to share your work to make our customers and your peers better everyday

Nice To Haves

Experience delivering these solutions in a cloud environment and experience working with cloud platforms (Azure a must, AWS and GCP nice to have)

Responsibilities

Integrate AI solutions across various domains, focusing on real-world applications
Incorporate generative AI, prebuilt AI services, and business logic into a solution to achieve the best result, and be able to articulate the process, challenges overcome, and impacts with others
Integrate AI models into broader enterprise applications, APIs and data workflows, leveraging established cloud services into solutions, focusing on efficiency, and understanding the pros and cons of build vs. buy options in a holistic architecture
Conduct experiments and comparative analysis to evaluate model performance, use deep skills in prompt engineering for generative AI problems or collaborate with data scientists to iterate and improve results
Leverage experience in data engineering, software development, generative AI, and LLMOPs/DevOps to implement end-to-end solutions that integrates insights and tools from the data science and data analytics teams
Use skills and experience in deploying production-grade AI applications to optimize for latency, accuracy, and scale. Establish reusable patterns and share with technical solution leaders
Use technical and practical experience with low/no-code tools such as Microsoft Copilot and Copilot Studio to build simple solutions to help simplify and scale AI for our customers
Stay updated on Azure cloud services, SaaS and PaaS, and understand how the changing landscape affects our customer journey
Outstanding communication skills, both written and verbal, to effectively collaborate with internal teams and present solutions to clients
Demonstrate ability to work in a client-facing capacity, understanding their needs and translating them into technical solutions