Senior AI Product Builder

Exiger•Richmond, VA

2d•Hybrid

About The Position

Exiger is seeking a Senior AI Product Builder to help shape and deliver its next generation of AI-powered Super Intelligence products. This role operates at the intersection of product, technology, and customer engagement. It combines customer discovery and product ownership with hands-on prototyping and technical collaboration; it is neither limited to traditional product management nor solely focused on engineering implementation. The position is based in Richmond, Virginia, or McLean, Virginia, with a hybrid work environment. The successful candidate will work directly with customers, business leaders, and internal stakeholders to understand complex business challenges, identify valuable product opportunities, and translate needs into practical AI-powered solutions. They will own initiatives from discovery and problem definition through prototyping, development, launch, and iteration, partnering with engineers, designers, data specialists, and other product builders along the way. The role involves designing and prototyping applications, intelligent agents, automations, and workflows using large language models, agentic frameworks, APIs, code, and AI-assisted development tools. The builder will collaborate on technical design and feasibility, explore techniques such as retrieval-augmented generation, tool calling, agent orchestration, prompt and context design, and model selection, and help evaluate AI features for accuracy, reliability, safety, and usefulness. They will also contribute to responsible AI experiences that consider security, privacy, customer data, and human oversight. Exiger describes its product development lifecycle as AI-enabled from research and idea exploration through coding, testing, documentation, and product improvement. AI Product Builders are expected to work across disciplines, engage stakeholders directly, test ideas early, and move from customer problems to useful working solutions while applying human judgment and accountability. Success includes building customer and team relationships, leading discovery, guiding initiatives through launch and iteration, making sound product and technical tradeoffs, and delivering measurable customer adoption, efficiency, or business value.

Requirements

Typically 4–7 years of relevant experience in product development, technical product ownership, AI application development, product engineering, solutions engineering, forward-deployed engineering, or a related field; demonstrated capability and ownership are valued over a specific number of years.
Meaningful experience working directly with customers, business stakeholders, or senior leaders to understand needs, gather feedback, influence decisions, and drive outcomes.
Demonstrated experience owning products or significant product initiatives from discovery through delivery and iteration.
Strong product judgment, including identifying valuable problems, prioritizing competing needs, and making informed tradeoffs.
Hands-on experience building or prototyping software applications, AI-powered tools, automations, or technical workflows.
Practical understanding of large language models and modern AI applications, their capabilities, limitations, and real-world use cases.
Familiarity with AI agents, RAG, tool calling, prompt engineering, model evaluation, or related AI development techniques.
Working knowledge of programming languages such as Python, JavaScript, or TypeScript, as well as APIs, data integration, and software development fundamentals.
Ability to collaborate effectively with engineers and participate meaningfully in technical discussions without owning every aspect of implementation.
Excellent verbal and written communication skills and confidence engaging customers and stakeholders at multiple organizational levels.
Ability to navigate ambiguity, challenge assumptions constructively, and bring structure to complex or loosely defined business problems.
Track record of taking initiative, experimenting with new approaches, and following through to deliver measurable results.

Nice To Haves

Experience at an AI-native company or building AI-first products.
Experience with enterprise B2B SaaS platforms or customer-facing enterprise software.
Experience with AI agent frameworks, vector databases, embedding models, evaluation tools, or multi-agent systems.
Familiarity with LangChain, LlamaIndex, Claude Code, Cursor, Codex, or similar AI development platforms.
Experience building and deploying applications using Python, JavaScript, TypeScript, SQL, or cloud services.
Experience in a customer-facing technical role such as Forward Deployed Engineer, Solutions Engineer, Product Engineer, or Technical Product Lead.
Familiarity with product collaboration tools such as Figma, Jira, Confluence, or Productboard.
Experience in government, defense, supply chain, procurement, risk management, compliance, or other complex enterprise environments.
A bachelor's degree in computer science, engineering, business, product management, or a related discipline, or equivalent practical experience.
Examples of products, applications, AI-powered workflows, prototypes, or initiatives brought to life, with details about the problems solved, stakeholder engagement, decisions, solutions, and impact.

Responsibilities

Work directly with customers, business leaders, and internal stakeholders to understand challenges, workflows, and opportunities.
Lead discovery conversations, workshops, product demonstrations, and feedback sessions with technical and nontechnical audiences.
Translate ambiguous business problems and customer requests into product opportunities, requirements, and actionable solutions.
Build stakeholder relationships, manage expectations, and communicate clearly with senior leaders and cross-functional teams.
Own product initiatives from discovery and problem definition through prototyping, development, launch, and iteration.
Partner with engineers, designers, data specialists, and other product builders to turn customer needs into AI-powered experiences.
Define product requirements, user journeys, workflows, success metrics, and acceptance criteria.
Prioritize opportunities based on customer impact, business value, feasibility, and available resources; make tradeoffs involving scope, speed, usability, complexity, and long-term value.
Test ideas with customers, incorporate feedback, and refine solutions before substantial development investment.
Use product analytics, customer feedback, and measurable outcomes to guide what to build, improve, or stop.
Drive cross-team alignment and keep initiatives moving as requirements and priorities change.
Design, prototype, and help deliver AI-powered applications, intelligent agents, automations, and workflows.
Use large language models, agentic frameworks, APIs, code, and AI-assisted development tools to explore and validate product ideas.
Collaborate with engineering teams on solution design, architecture, integrations, and technical feasibility.
Experiment with RAG, tool calling, agent orchestration, prompt and context design, and model selection.
Assess when AI is appropriate and when traditional software or deterministic workflows are more reliable.
Partner with engineers to define evaluations, test cases, and quality measures for AI features, including accuracy, reliability, safety, and usefulness.
Identify technical limitations, troubleshoot issues, and help determine practical solutions.
Contribute directly to prototypes, automations, and technical workflows while partnering with engineers on production implementations.
Help develop responsible AI experiences that account for security, privacy, customer data, and appropriate human oversight.
Present product concepts, demonstrations, recommendations, and outcomes to technical and nontechnical stakeholders.
Help shape Exiger's Super Intelligence product vision and improve how the organization builds products with AI.