Mid-Level AI Engineer (NOT SENIOR)

Job Title: Mid-Level AI Engineer (NOT SENIOR)

Location: Washington, DC - Onsite 5 days per week (local candidates only - must live in Washington, DC area)

Work Arrangement: Onsite

Interview Mode: Video + In-Person Interview

Experience Required: 4-7 years

Position Overview


The AI Engineer will be part of a Tech Consulting firm's Forward Deployed Engineering team supporting the Client's AI-Assisted SDLC Pilot Program. Working closely with the onsite AI Architect, this role is embedded directly alongside the Bank's development squads - configuring AI tooling, operating governance controls, and enabling developers through daily paired coding sessions. The AI Engineer reports to the Tech Consulting Company Engagement Lead and plays a critical role in ensuring the pilot produces measurable, evidence-based productivity outcomes.


Must-Have Skills

• 5+ years of software engineering experience across all technologies and back-end technologies
• Hands-on experience with AI coding assistants (e.g., GitHub Copilot, Claude Code, Cursor, Amazon Q Developer) in day-to-day development workflows
• Strong proficiency in modern web frameworks, RESTful APIs, and at least one major cloud platform (AWS, Azure, or GCP)
• Solid understanding of CI/CD pipelines, Git workflows, pull request reviews, and automated testing practices
• Experience with static analysis tools (SAST), code quality gates, and security scanning in enterprise development environments
• Ability to write clear technical documentation, training materials, and process guides
• Bachelor's degree in Computer Science, Software Engineering, or a related field
• Must speak clear American English

Key Responsibilities

• Participate in codebase assessments to evaluate the Bank's existing technology stack, development workflows, and AI readiness (multi-programming languages - Python and Java to be able to look at code base)
• Configure and maintain squad development environments, including AI coding tools, context files, and agent configurations within the Bank's infrastructure
• Set up and operate governance tooling including PromptBOM logging, SAST rulesets for AI-generated code, and secrets scanning pipelines (Python)
• Embed daily within Bank engineering squads during pilot execution - reviewing AI-flagged pull requests, pair-programming, and coaching developers on AI-assisted workflows
• Build and refine custom agents, prompt libraries, and steering files based on pilot learnings and squad feedback
• Document ways of working, training materials, and the AI-SDLC playbook content in collaboration with the AI Architect
• Transition from embedded driver to coaching role during the Optimization & Expansion phase, guiding new squads through onboarding
• Harden the agent library and toolchain configurations for production-readiness during capability transfer
• Support the train-the-trainer program by teaching Bank engineers to independently configure, maintain, and extend the AI tooling

Additional Skills (Plus)

• Experience with prompt engineering or building custom AI agents/skills
• Familiarity with developer productivity measurement frameworks (e.g., SPACE, DORA metrics)
• Prior experience working on client-embedded or forward-deployed engineering engagements
• Knowledge of compliance and governance requirements in regulated industries (financial services, government)
• Experience mentoring or training junior developers or conducting technical workshops

Candidate Preferences

• Prefer candidates with investment banking, investment management, asset management experience (retail/commercial bank experience is also acceptable)