AI Implementation Specialist

Parsons Corporation•USA VA (Virtual Office), VA

2d•$63,600 - $111,300•Hybrid

About The Position

Parsons is seeking a hands-on AI Implementation Specialist to help identify, prototype, and apply practical AI solutions to business and operational challenges across the enterprise. In this role, you will work directly with stakeholders to understand workflows, identify opportunities where enterprise AI capabilities can improve speed, quality, and decision-making, and help implement those solutions in real business contexts. The ideal candidate combines strong familiarity with modern generative AI tools and applied AI concepts with the ability to translate business problems into useful, implementable solutions. This is not a pure research role and not a full-stack engineering role. It is focused on practical application, experimentation, workflow enablement, and measurable business impact. Candidates located within the DMV area are preferred.

Requirements

Bachelor’s degree in STEM or another related field
At least 3+ years of hands-on experience building, applying, or implementing AI, machine learning, automation, analytics, or data-driven solutions through professional work, academic projects, or substantial independent work
Ability to obtain and maintain an active Secret or Top Secret clearance to support sensitive DoD/IC projects
Solid understanding of generative AI applications, prompt design, retrieval-augmented generation, machine learning lifecycles, and data analytics
Experience using modern AI platforms or tools to create AI assistants, knowledge-grounded workflows, task automation, or multimodal solutions
Ability to assess business problems and determine whether they are best addressed with generative AI, traditional machine learning, automation, analytics, or other technical approaches
Demonstrated ability to communicate technical AI concepts clearly to non-technical audiences and support adoption in practical settings
Experience testing, benchmarking, and evaluating AI outputs in real workflows or applied use cases

Nice To Haves

Strong interest in emerging AI capabilities and how they can be applied pragmatically to real business problems
Experience with prompt engineering, output evaluation, and iterative improvement of generative AI workflows
Familiarity with enterprise AI platforms, secure AI environments, or regulated technology environments
Experience with AI workflow automation, orchestration tools, APIs, or low-code automation platforms
Familiarity with multimodal AI capabilities such as image generation, image analysis, or document understanding
Ability to assess implementation feasibility, data readiness, and operational fit for AI use cases
Ability to interpret AI-driven insights and use data to support business and strategic decision-making

Responsibilities

Work directly with business and operational teams to understand workflows, pain points, and opportunities for AI-driven improvement
Identify where enterprise AI capabilities such as custom AI assistants, retrieval-based knowledge tools, workflow automation, and multimodal AI features can be applied effectively
Translate business needs into practical AI use cases, prototype concepts, and implementation approaches
Evaluate whether business problems are best addressed using generative AI, automation, analytics, traditional machine learning, or other technical methods
Configure, test, and benchmark AI-enabled workflows in real or representative business scenarios to assess usability, performance, and impact
Support implementation of AI solutions by helping set up prompts, knowledge sources, workflow steps, and evaluation approaches
Collaborate with software engineers, data scientists, analysts, and business stakeholders to support integration of AI capabilities into tools and processes
Conduct needs assessments, feasibility reviews, and business case analyses for AI adoption
Help users apply AI tools effectively by providing practical guidance, documentation, and user support
Create clear documentation, playbooks, and user guides for prototypes, workflows, and repeatable use cases
Promote responsible AI use by considering fairness, transparency, security, and regulatory compliance in solution design and rollout