Full stack Software Engineer (AI Enablement Engineer)

Hiring Full stack Software Engineer (AI Enablement Engineer) Location: Rockville, MD or McLean, VA (Hybrid) Only Local DC/VA/MD who can take Assessment and for Onsite interview Pay range: .-55/hr DOE on W2 Job Description: This position supports a newly approved AI Finance Readiness initiative focused on improving finance and administrative business processes through AI-enabled discovery, proof-of-concepts, and targeted implementations. The engineer will partner with business stakeholders, architects, and technical teams to evaluate opportunities across systems such as Workday Financials, FlexTrack, and other finance-related platforms. The goal is not to build foundational AI models, but rather to determine where modern AI technologies can improve workflows, efficiency, analytics, and decision-making. Key Focus Areas AI-Driven Business Process Discovery Evaluate finance and administrative workflows to identify opportunities for AI-enabled improvements. Conduct discovery sessions with business stakeholders and help assess feasibility of potential AI solutions. Support POCs and pilot initiatives that may ultimately lead to production implementations. Analyze existing processes and determine whether AI enhancements or alternative workflows provide the greatest value. Technology Environment Strong engineering foundation in: Java AWS Python Exposure to modern AI platforms and tools such as: Claude Amazon Bedrock LLM-based solutions Experience with analytics platforms, automation tools, and SaaS integrations is beneficial but not required. Previous experience with RPA or workflow automation initiatives is highly relevant, as the organization views AI as a natural evolution of past automation efforts. What They Are NOT Looking For Not seeking an AI researcher or someone building foundational LLMs. Not looking for a "unicorn" with every emerging AI skill. Not interested in candidates who simply leverage AI-generated code without understanding architecture, tradeoffs, and implementation details. This is not a pure data science or machine learning engineering role. Ideal Candidate Profile Must-Have Characteristics Strong senior-level software engineer with solid Java, AWS, and Python experience. Demonstrated curiosity and active investment in learning modern AI technologies. Ability to quickly evaluate AI use cases and determine technical feasibility. Strong communication and stakeholder engagement skills. Comfortable translating business problems into practical technical solutions. Able to articulate pros, cons, risks, and implementation approaches during POC discussions. Nice-to-Have Experience SaaS integration experience. Workday Financials or enterprise finance systems exposure. FlexTrack experience. Analytics platform integration experience. RPA or intelligent automation background. Personality & Mindset Strong engineering judgment and architectural thinking. Consultative approach with business users. Comfortable navigating environments where stakeholders have differing opinions on AI solutions. Learning-oriented and adaptable to rapidly evolving AI technologies. Preference for senior engineers who can operate independently, though exceptional mid-level candidates with strong learning agility will also be considered. Interview Screening Themes Engineering Fundamentals Depth in Java, AWS, and Python. Architecture and design thinking. Ability to evaluate technical tradeoffs. AI Adoption & Learning Mindset How are they using Claude, Bedrock, Copilot, or similar tools? Examples of AI-enabled solutions they have explored or implemented. How they stay current with emerging AI technologies. Business Partnership Experience gathering requirements and working directly with business stakeholders. Ability to challenge assumptions and assess feasibility. POC & Innovation Experience Examples of leading discovery efforts, pilots, or proof-of-concepts. How they evaluated success criteria and implementation options. Communication Ability to explain technical concepts to non-technical audiences. Experience influencing architects, business leaders, and engineering teams.