AI Coding Tools Engineer

Ampcus Inc.•Chantilly, VA

1d•Onsite

About The Position

The AI Coding Tools Engineer (GenAI & Agentic Systems) evaluates, pilots, operationalizes, maintains, and scales adoption of secure AI coding assistant tools across the enterprise.

Requirements

Minimum 2 years of experience with leading AI Coding Assistants.
Minimum 3–5 years of experience in software engineering, developer experience engineering, platform engineering, or related roles.
Experience integrating or evaluating LLM powered developer tools (e.g., code completion, chat-based programming assistance, test generation, refactoring tools).
Understanding of NIST compliance and government cloud environments.
Familiarity with enterprise DevSecOps practices, modern IDEs, and secure software development lifecycles.

Nice To Haves

Direct experience leading enterprise adoption of AI coding assistants (pilot design, rollout planning, governance alignment).
Hands on experience with Amazon Bedrock GovCloud, Azure OpenAI (Gov), and/or Vertex AI (Assured Workloads) for production workloads.
Experience building multi-step agent workflows on Bedrock Agents, implementing Bedrock Guardrails, or building RAG/semantic search systems via Vertex AI Search.
Experience supporting ATO artifacts and design/testing of controls.

Responsibilities

Conduct structured evaluations of leading enterprise AI coding assistants, including features, model performance, security, integration complexity, and developer ergonomics.
Integrate coding assistants into IDEs (VS Code), terminals/CLI workflows, and source control ecosystems.
Configure AI guardrails, including content filtering, prompt shielding, and role-based access controls aligned with enterprise and NIST requirements.
Work with Security Team to prepare ATO evidence, including SSP updates, control narratives, risk registers, and continuous monitoring artifacts.
Work with Training and Enablement Team to develop training, compliance, and end-user/best practice guides.
Support Coding Assistant “office hours” to support developer enablement and accelerate adoption.
Collect user feedback, track adoption metrics, and iteratively refine usage patterns for different developer roles.
Monitor platform health and guardrail performance.
Support analysis and remediation of integration or platform issues impacting the coding assistants.
Track, evaluate, and support application of coding assistant updates and patches.