Software Jobs in McLean, VA (Now Hiring) — 1,273 open — Page 26

Role Overview

We are seeking an AI Enablement Engineer to join our new Corporate AI Enablement & Efficiency team — the group responsible for turning AI from a buzzword into everyday leverage for the entire company. You will design and build the automations, integrations, and AI agents that connect our applications, eliminate manual work, and help every team do more with the tools they already have. Your work will directly shape how a 1,000-person organization adopts AI: safely, measurably, and at scale.

You will wire up production workflows, connect systems through APIs, and stand up MCP servers, AI skills, and agents that give teams reliable, governed access to large language models. Other days you will be out in the business, spotting the manual, repetitive work worth automating and shipping solutions that stick. Throughout, you will build like an engineer: real error handling, observability, evaluations, and guardrails — and you will keep Security and Data close so everything you ship stays compliant. 

You will work at the frontier of applied AI: agents, MCP, retrieval, and orchestration with the autonomy to build real things that of colleagues. If you love turning messy manual processes into elegant solutions and want to help define how a company puts AI to work, this is an exciting opportunity to make a meaningful impact. 

Role Responsibilities 

• Design, build, and maintain end-to-end automations and integrations, connecting the company's applications, data, and AI services.
• Integrate systems through APIs and webhooks — handling authentication, rate limits, retries, and idempotency.
• Build AI-powered capabilities using large language models: structured outputs, retrieval-augmented generation (RAG), and tool / function-calling that automate real business processes.
• Develop and maintain MCP servers and reusable AI skills and agents that give teams safe, governed access to internal systems and data.
• Instrument everything you build with logging, monitoring, evaluations, and guardrails, and resolve failures before users feel them.
• Partner with teams across the company to identify high-value automation and AI use cases, then scope, prioritize, and deliver them.
• Work with the Security and Data teams to ensure responsible, compliant handling of data, secrets, and AI usage.
• Contribute to build-vs-buy evaluations and help reduce software and license waste by consolidating or replacing tools with automation.
• Create clear documentation, templates, and enablement materials so your work scales beyond you.
• Set technical patterns, standards, and architecture for the team's automation and agent platform, and mentor other engineers.
• Own the architecture of the AI and automation estate and lead the team's most complex, cross-functional initiatives. (Applies if the role is filled at the Lead level.)
• Perform other duties as assigned to meet team and organizational needs.

Required Skills / Abilities 

• 4+ years building integrations, automations, or software in a professional environment including production work with LLMs or AI agents.
• Hands-on experience with workflow-automation.
• Strong API fluency (REST / JSON, OAuth, webhooks) and the ability to read and write code in Python, Go, JavaScript / TypeScript or similar.
• Practical experience building with large language models: prompting, structured outputs, and at least one of RAG, tool / function-calling, or agents.
• A production mindset - error handling, logging and observability, testing or evaluations, and secure handling of secrets and sensitive data.
• Ability to work directly with non-technical colleagues: understanding a business process and translating it into a reliable, well-documented automation.
• Understanding of data privacy, security, and responsible-AI considerations, and a habit of partnering with Security and Data teams.

Ideal Qualifications

• Experience building or deploying MCP servers, AI agents, or custom AI skills.
• Familiarity with the modern AI stack: orchestration frameworks, vector databases, and evaluation tooling.
• A portfolio of shipped automations or agents that shows production quality, not just prototypes.
• Experience integrating common business systems and their APIs (HRIS, ITSM, CRM, finance, and collaboration suites).
• Exposure to enterprise AI tools (AI copilots, chat assistants) and helping teams adopt them effectively.
• A track record of reducing software or license spend through automation or tool consolidation.
• Experience setting standards, mentoring engineers, or owning build-vs-buy and platform decisions.
• Strong written communication and documentation skills, and a bias toward making your work reusable.